{"id":"W6931604878","doi":"10.5683/sp3/ifyzku","title":"Low Water Lake Ontario. 1:50,000. Map Sheet 041P04, ed. 3, 1996","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; Aerial photography; Natural (archaeology); Raster graphics; Topographic map (neuroanatomy); Natural resource; Geographic information system; Government (linguistics)","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":[0.0004002805,0.001571451,0.001132702,0.00443828,0.001227204,0.002375271,0.001622456,0.0005014545,0.1218831],"category_scores_gemma":[0.002403134,0.0009244815,0.000596491,0.02114713,0.0003730914,0.0008707362,0.000877735,0.0007231399,0.0793017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009298353,"about_ca_system_score_gemma":0.0140594,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9102055,"about_ca_topic_score_gemma":0.9420916,"domain_scores_codex":[0.999473,0.00002265694,0.000049807,0.0001126796,0.0002219799,0.0001198293],"domain_scores_gemma":[0.9984817,0.00009574349,0.000179587,0.0001490916,0.0009276632,0.000166227],"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":[0.00002011288,0.00000429161,0.001551829,0.0003211151,0.000009827153,0.00001585924,0.00004362173,0.00008048415,0.00003319135,0.0001964198,0.9931722,0.004551103],"study_design_scores_gemma":[0.00005107655,0.000004146616,0.02940313,0.0002007246,0.00001570767,0.00002761308,0.0001506932,0.0001167536,0.00009329712,0.000166272,0.9697547,0.00001576889],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001061689,0.00004969832,0.00001992909,0.00002839326,0.000007338994,0.000006360608,0.9979697,0.00005540961,0.001756921],"genre_scores_gemma":[0.0007560534,0.0001974628,0.0001877846,0.00001976191,0.000005093539,0.00006090674,0.9908038,0.0000502756,0.007918889],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1218831,"threshold_uncertainty_score":0.4077395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01334717355044535,"score_gpt":0.2475048830014448,"score_spread":0.2341577094509995,"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."}}