{"id":"W6969026082","doi":"10.5683/sp3/3bct76","title":"Chabbie Lake Ontario. 1:50,000. Map Sheet 032E12, ed. 2, 1990","year":2021,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Georeference; General partnership; Natural (archaeology); Raster graphics; Aerial photography; Topographic map (neuroanatomy); Viewshed analysis; 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":[0.0004511702,0.00202236,0.001366462,0.005033782,0.001704704,0.002981693,0.002087384,0.00070206,0.1396486],"category_scores_gemma":[0.002684829,0.0009967729,0.0006983005,0.02341476,0.00048289,0.001152145,0.001034864,0.0010681,0.1021636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01362497,"about_ca_system_score_gemma":0.02148889,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9596739,"about_ca_topic_score_gemma":0.9774139,"domain_scores_codex":[0.9993379,0.00002704669,0.00004668621,0.0001459195,0.0002758994,0.0001664987],"domain_scores_gemma":[0.997785,0.0001105126,0.0001619398,0.0002259833,0.001496604,0.0002200674],"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":[0.00001357739,0.000003308771,0.0006496823,0.0002227755,0.000007451518,0.00000947971,0.0000282451,0.00005952185,0.00002791508,0.0001554244,0.9960453,0.00277731],"study_design_scores_gemma":[0.00003970123,0.000003379535,0.01495328,0.0001770447,0.00001184143,0.00001989518,0.0001305623,0.0001065602,0.00008497322,0.0001701025,0.9842846,0.00001802002],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006160037,0.00004972648,0.0000186803,0.00002427069,0.000008890275,0.000005413463,0.9981514,0.0000729482,0.001607101],"genre_scores_gemma":[0.000594577,0.0001489273,0.0001808718,0.00002402859,0.000004675811,0.00004690861,0.9933879,0.00007262549,0.005539507],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1396486,"threshold_uncertainty_score":0.4671711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0174678286446103,"score_gpt":0.253319490905898,"score_spread":0.2358516622612877,"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."}}