{"id":"W6950656008","doi":"10.5683/sp3/rprtnk","title":"Mead Ontario. 1:50,000. Map Sheet 042G05, ed. 3, 1987","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); Viewshed analysis; Government (linguistics); Aerial photography; Digital mapping","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":[0.0004146326,0.001608678,0.00114487,0.004812056,0.0013294,0.002552483,0.001442586,0.0004880702,0.1490937],"category_scores_gemma":[0.002317341,0.0009062069,0.000520002,0.01935177,0.0003843624,0.001003995,0.0009120139,0.000754162,0.1072383],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008125823,"about_ca_system_score_gemma":0.01274422,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8635578,"about_ca_topic_score_gemma":0.9231862,"domain_scores_codex":[0.9993902,0.00002981095,0.000048477,0.0001369855,0.0002524745,0.0001420294],"domain_scores_gemma":[0.99848,0.0001010273,0.0001579934,0.0001716122,0.0009162404,0.0001731033],"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":[0.00001412207,0.000003176158,0.0007941835,0.0002400176,0.000007049035,0.00001050031,0.00003293098,0.0000523488,0.00002968024,0.0001824414,0.9952275,0.003406022],"study_design_scores_gemma":[0.00002805277,0.000002603495,0.01305509,0.00014212,0.000008853002,0.00001845935,0.0001234264,0.00006990139,0.00007513721,0.0001317163,0.9863331,0.00001141979],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008883666,0.00006053121,0.00002446445,0.00002291095,0.000009249482,0.000006454587,0.9973366,0.00007076208,0.002380231],"genre_scores_gemma":[0.0007187814,0.0001746939,0.0002317052,0.00002202771,0.000006016059,0.00005151049,0.9913005,0.00006896778,0.007425739],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1490937,"threshold_uncertainty_score":0.4987683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02033254976919685,"score_gpt":0.2614110591919092,"score_spread":0.2410785094227124,"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."}}