{"id":"W6969436222","doi":"10.5683/sp3/wdldhs","title":"Nottawasaga Bay Ontario. 1:50,000. Map Sheet 041A09, ed. 3, 1979","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); Aerial photography; Raster graphics; Bay; Topographic map (neuroanatomy); 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":[0.0004246457,0.001905151,0.001381479,0.004875075,0.00153625,0.00302381,0.001825321,0.0006055159,0.1368007],"category_scores_gemma":[0.002472086,0.0009658612,0.0006659127,0.02290911,0.0004975098,0.001152706,0.00109228,0.0009758422,0.1107745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01031335,"about_ca_system_score_gemma":0.01744966,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9151044,"about_ca_topic_score_gemma":0.9530356,"domain_scores_codex":[0.9993063,0.00002725138,0.00005627657,0.0001649225,0.000280078,0.0001652025],"domain_scores_gemma":[0.9978923,0.000110734,0.0001929815,0.0002394908,0.001344948,0.0002195822],"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":[0.00001910487,0.000003752628,0.000959919,0.0002861412,0.000009555111,0.00001341235,0.00004352163,0.00006763454,0.00004503813,0.0002154307,0.9952403,0.003096187],"study_design_scores_gemma":[0.00003447861,0.000002853576,0.01329284,0.0001389933,0.000009913243,0.00002011461,0.0001443588,0.00006543445,0.0000852333,0.0001487004,0.986043,0.00001407957],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007177828,0.00004777006,0.00001792485,0.00002429406,0.00001190824,0.000004722296,0.9979523,0.00006128419,0.001807862],"genre_scores_gemma":[0.0006403823,0.0001628576,0.0001626774,0.0000185196,0.0000058013,0.00004028613,0.9927735,0.000075147,0.006120827],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1368007,"threshold_uncertainty_score":0.4576439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0175832917264187,"score_gpt":0.2548490416706883,"score_spread":0.2372657499442696,"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."}}