schema · 20 fields

Storing and comparing massive output datasets from various global climate models (GCMs) to analyze the range of projections for specific regions (e.g., sea-level rise in coastal cities).

Automate extraction for "Storing and comparing massive output datasets from various global climate models (GCMs) to analyze the range of projections for specific regions (e.g., sea-level rise in coastal cities).". Extract structured, evidence-grounded data points directly from hundreds of papers with source page coordinates.

Build Your Own Database Free

Schema Field Definitions (20)

Field Name	Data Type	Description
gcm_name	string	The official name of the Global Climate Model (GCM) used for the projection. Example: 'HadGEM3-GC31-LL'.
model_version	string	The specific version identifier of the GCM used. Example: 'v1.0'.
model_institution	string	The institution or modeling group that developed the GCM. Example: 'NCAR', 'Met Office'.
emissions_scenario	string	The climate change mitigation or shared socioeconomic pathway (SSP) scenario used. Must be one of: RCP2.6, RCP4.5, RCP6.0, RCP8.5, SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5.
experiment_id	string	The standardized CMIP experiment identifier. Example: 'historical', 'ssp585'.
target_city_name	string	The name of the coastal city or region being analyzed. Example: 'New York City', 'Shanghai'.
target_latitude	number	The central latitude of the analyzed area in decimal degrees.
target_longitude	number	The central longitude of the analyzed area in decimal degrees.
projected_variable	string	The primary climatic variable being projected. Must be one of: Sea_Level_Rise, Surface_Air_Temperature, Precipitation, Ocean_pH, Extreme_Heat_Days.
projection_type	string	The type of output statistic reported for the variable. Must be one of: Mean, Median, P5, P95, Max, Min.
projection_year	number	The target future year for the projection, as an integer. Example: 2100.
baseline_period_start_year	number	The start year of the historical baseline period used for comparison, as an integer. Example: 1995.
baseline_period_end_year	number	The end year of the historical baseline period used for comparison, as an integer. Example: 2014.
is_relative_change	boolean	Is the projection value reported as a relative change from the baseline period (true) or an absolute magnitude (false)? Must be true or false.
projection_value	number	The magnitude of the projected value (change or absolute value) as a floating-point number.
projection_value_unit	string	The unit for the projection value. Standardize units if possible. Examples: 'm', 'cm', '°C', 'mm/day'.
uncertainty_level	number	The reported standard deviation, uncertainty range, or error margin associated with the projection, as a floating-point number.
uncertainty_level_unit	string	The unit for the uncertainty level. This should match the projection_value_unit. Examples: 'm', '°C'.
confidence_interval_percent	number	The confidence interval percentage associated with the uncertainty calculation (e.g., 90 or 95), as an integer.
doi	string	The Digital Object Identifier (DOI) or a full bibliographic reference for the source paper.

Data Verification Status Taxonomy

To maintain rigorous scientific standards, Sci-database differentiates between automated signals and human audit:

Extracted

Value located and extracted from the full-text PDF by the Kateeb engine.

Model-Agreed

An independent second model produced a compatible value during automated second-pass review.

Human-Reviewed

A named researcher audited the value against the visual page coordinates.

Benchmark-Validated

Performance evaluated against a standardized, published evaluation protocol.

Replicated

An independent external research group reproduced the extraction and experimental result.

Premium Database for Sale

A high-quality, large-scale database curated by a community member is available for purchase.

This "Golden" database contains 29 papers and is ready for in-depth analysis.

Storing and comparing massive output datasets from various global climate models (GCMs) to analyze the range of projections for specific regions (e.g., sea-level rise in coastal cities).

Schema Field Definitions (20)

Data Verification Status Taxonomy

Dataset provenance & access

Storing and comparing massive output datasets from various global climate models (GCMs) to analyze the range of projections for specific regions (e.g., sea-level rise in coastal cities). — published dataset