{"id":"W6969114010","doi":"10.5683/sp3/bjjhly","title":"River Jordan (West) British Columbia. 1:50,000. Map Sheet 092C08, ed. 1, 1955","year":2022,"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; Topographic map (neuroanatomy); Aerial photography; Government (linguistics); Viewshed analysis","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":[0.0003437892,0.001616652,0.001149217,0.005087676,0.001762056,0.003806931,0.001488387,0.0005618629,0.1270153],"category_scores_gemma":[0.002025262,0.0008370222,0.0004583644,0.02224406,0.0004025238,0.00104513,0.0009470716,0.001247695,0.09403526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007831049,"about_ca_system_score_gemma":0.01525188,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9271605,"about_ca_topic_score_gemma":0.9601578,"domain_scores_codex":[0.9994721,0.00002265921,0.00003900774,0.000140847,0.0001849946,0.0001404491],"domain_scores_gemma":[0.9983291,0.00007343301,0.0001094859,0.0001678475,0.001161652,0.0001585327],"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":[0.00001691723,0.000003748693,0.0007371478,0.0001684354,0.000007539385,0.00001385252,0.00002950007,0.00006172884,0.000027587,0.0001884291,0.9945155,0.004229553],"study_design_scores_gemma":[0.0000246114,0.000002124157,0.01295047,0.0001914661,0.000008134272,0.00002119362,0.0001805338,0.00008680423,0.0000943535,0.0001637678,0.9862595,0.00001702358],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001736006,0.000107378,0.00002885308,0.00003180405,0.00001932795,0.000007463907,0.9956664,0.0001469064,0.003818277],"genre_scores_gemma":[0.001437906,0.0002408084,0.0002177652,0.00003397056,0.000006934485,0.00004995639,0.9857364,0.0001380785,0.01213816],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1270153,"threshold_uncertainty_score":0.4249085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01192812484260036,"score_gpt":0.2419736399630233,"score_spread":0.230045515120423,"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."}}