{"id":"W6931954653","doi":"10.5683/sp3/qunl8l","title":"Jarvis River (West) Ontario. 1:50,000. Map Sheet 052A03, ed. 1, 1958","year":2021,"lang":"en","type":"dataset","venue":"Borealis","topic":"Body Composition Measurement Techniques","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Georeference; General partnership; Aerial photography; Raster graphics; Natural (archaeology); Topographic map (neuroanatomy); Viewshed analysis; Geographic information system","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":[0.0004022054,0.001320629,0.00115983,0.003347587,0.001264116,0.00259428,0.001445258,0.0005025836,0.1075838],"category_scores_gemma":[0.002407751,0.000802805,0.0006119244,0.01484692,0.0004645846,0.0008826362,0.0009122208,0.0008244624,0.08899835],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00703299,"about_ca_system_score_gemma":0.01416366,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8942989,"about_ca_topic_score_gemma":0.9464198,"domain_scores_codex":[0.9994485,0.0000296667,0.00004557664,0.0001578326,0.0001983138,0.0001201128],"domain_scores_gemma":[0.9985624,0.0001012866,0.0001324353,0.0001876915,0.0008699408,0.0001462206],"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":[0.00002464502,0.000003324122,0.001238691,0.0003178825,0.00001170671,0.00001481484,0.00005317459,0.00006588258,0.00003737516,0.0002654653,0.9938607,0.004106274],"study_design_scores_gemma":[0.00003442645,0.000002777918,0.01399651,0.0001641913,0.000009993313,0.00002230251,0.0001280111,0.00005578396,0.00006516371,0.0001711896,0.9853374,0.00001224443],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001139413,0.00008890936,0.00003637184,0.00003195402,0.00001389718,0.00000621881,0.9973877,0.0001059991,0.00221506],"genre_scores_gemma":[0.001034633,0.0002389671,0.0002664889,0.00002813526,0.000008640684,0.00005106872,0.9907544,0.0001044533,0.007513402],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1075838,"threshold_uncertainty_score":0.3599035,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02492463296969432,"score_gpt":0.2769514020364546,"score_spread":0.2520267690667602,"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."}}