{"id":"W6932106094","doi":"10.5683/sp3/0lsoxy","title":"Parkhill Ontario. 1:50,000. Map Sheet 040P04, ed. 5, 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; Raster graphics; Natural (archaeology); Digital mapping; Geographic information system; Aerial photography; 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":[0.0004508744,0.001998923,0.001476908,0.005233618,0.001489701,0.003123641,0.00193293,0.0006527226,0.174146],"category_scores_gemma":[0.002545316,0.001093102,0.0006661187,0.02226492,0.0005121827,0.001357683,0.001096592,0.0009881081,0.1567191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008437736,"about_ca_system_score_gemma":0.01393357,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8227242,"about_ca_topic_score_gemma":0.8938889,"domain_scores_codex":[0.9992601,0.00003256061,0.00006188024,0.0001753189,0.0003020207,0.0001681662],"domain_scores_gemma":[0.9981276,0.0001294951,0.0001866349,0.0002432706,0.001101016,0.0002119045],"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":[0.00001451186,0.000003329645,0.0005561125,0.0002621036,0.000007137038,0.0000100824,0.00002731985,0.00005313899,0.00003594601,0.0001838172,0.996287,0.002559509],"study_design_scores_gemma":[0.00003008323,0.000002564014,0.008154317,0.00013281,0.00000875602,0.0000183037,0.00009237135,0.00005455406,0.00007501971,0.0001518951,0.9912667,0.00001260857],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004167149,0.00003713111,0.00001711383,0.00001682634,0.000008364812,0.000003564282,0.9983632,0.00006685595,0.00144526],"genre_scores_gemma":[0.0003479328,0.0001184564,0.0001426102,0.00001532794,0.000004619964,0.00003233683,0.9947004,0.00006999418,0.004568344],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1772758,"threshold_uncertainty_score":0.5825764,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0179853779797426,"score_gpt":0.256203440807006,"score_spread":0.2382180628272634,"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."}}