{"id":"W6931689157","doi":"10.5683/sp3/wqewt5","title":"Timagami (West) Ontario. 1:50,000. Map Sheet 031M04, ed. 1, 1962","year":2021,"lang":"en","type":"dataset","venue":"Borealis","topic":"Prenatal Screening and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Georeference; General partnership; Raster graphics; Natural (archaeology); Digital mapping; Aerial photography; Geographic information system; Government (linguistics); Orthophoto","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":[0.0004055011,0.001467429,0.001096109,0.004010196,0.001345053,0.002588765,0.001387949,0.0005112409,0.15421],"category_scores_gemma":[0.002911659,0.0008007052,0.0006283284,0.01844675,0.0004573796,0.0009144167,0.0009782005,0.000791739,0.1055641],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009953005,"about_ca_system_score_gemma":0.01789967,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9347243,"about_ca_topic_score_gemma":0.9626905,"domain_scores_codex":[0.9993901,0.00002953143,0.00004890922,0.0001532207,0.0002314753,0.000146684],"domain_scores_gemma":[0.9982836,0.0001062011,0.0001650959,0.0001808123,0.001057904,0.0002063528],"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":[0.00002280677,0.00000314902,0.001190021,0.0003233217,0.00001068876,0.00001537449,0.00004967372,0.00007184861,0.0000404342,0.0002720653,0.9944306,0.00356994],"study_design_scores_gemma":[0.00003727298,0.000003086705,0.01573202,0.0001757868,0.00001222393,0.00002460766,0.0001440659,0.00007220203,0.00008517626,0.0001621186,0.9835382,0.00001315145],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000954663,0.0000818536,0.00002622786,0.00003686294,0.00001228084,0.000006706277,0.9970171,0.00007503197,0.002648378],"genre_scores_gemma":[0.001134577,0.0002909067,0.0002558976,0.00003445076,0.000009707984,0.00005721506,0.986849,0.0001010977,0.01126729],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.15421,"threshold_uncertainty_score":0.5158839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01771754954945787,"score_gpt":0.2680427636472761,"score_spread":0.2503252140978182,"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."}}