{"id":"W6999102992","doi":"","title":"Canada VMap1, Library 37: Miscellaneous Population Area Features","year":2016,"lang":"en","type":"other","venue":"The Faculty Digital Archive (New York University)","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Scale (ratio); Population; Product (mathematics); Geographic information system; Base (topology); Natural resource; Natural (archaeology)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004728028,0.0009562042,0.0006832604,0.007566248,0.003568296,0.003803278,0.001994224,0.000401152,0.2573299],"category_scores_gemma":[0.003892297,0.000585466,0.0004867458,0.02839109,0.0004518405,0.00131905,0.001374118,0.0005989142,0.1025508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01726871,"about_ca_system_score_gemma":0.05785386,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9656436,"about_ca_topic_score_gemma":0.9700429,"domain_scores_codex":[0.9989845,0.00002767933,0.00003912676,0.0001137175,0.000642443,0.0001923909],"domain_scores_gemma":[0.9963841,0.0001353095,0.0001123752,0.0001938651,0.002829943,0.0003443641],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000210311,0.000008539169,0.001102642,0.0001535251,0.000003539149,0.0000317331,0.0002004913,0.0001361006,0.00008642048,0.001679779,0.9577589,0.03881725],"study_design_scores_gemma":[0.000005090045,0.000003257268,0.008045139,0.00005324784,0.000004272808,0.00003371636,0.0002057608,0.0001273815,0.0001768352,0.0002466025,0.9910841,0.00001449907],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.002750211,0.0005285343,0.001212848,0.0005168477,0.0001961754,0.0002875694,0.6686403,0.002824086,0.3230435],"genre_scores_gemma":[0.02169567,0.002045907,0.006554005,0.0002998775,0.0001047491,0.0004126302,0.4705812,0.002752693,0.4955534],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.2573299,"threshold_uncertainty_score":0.8608543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01368918050447091,"score_gpt":0.1982662609316057,"score_spread":0.1845770804271348,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}