{"id":"W6894342951","doi":"10.5683/sp3/wkfxyn","title":"Cartier Lake Saskatchewan. 1:50,000. Map Sheet 073P01, ed. 1, 1973","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; Aerial photography; Topographic map (neuroanatomy); Government (linguistics); Digital mapping; 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":[0.0004265377,0.002056521,0.001238125,0.004634392,0.001003824,0.003333721,0.001730533,0.0007150611,0.23578],"category_scores_gemma":[0.002394326,0.001039119,0.0007469207,0.02486274,0.0003884118,0.001640898,0.001257573,0.001320861,0.2285105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005591203,"about_ca_system_score_gemma":0.0125388,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7474222,"about_ca_topic_score_gemma":0.8404232,"domain_scores_codex":[0.9994772,0.0000358263,0.00004705409,0.0001390353,0.0001666228,0.0001342721],"domain_scores_gemma":[0.9982952,0.0001234928,0.0001095562,0.000274706,0.001035711,0.0001612832],"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":[0.00001678746,0.000003146164,0.0004521584,0.000161963,0.00001143518,0.00001127034,0.00001893535,0.00007988479,0.00004162903,0.0001923573,0.9957349,0.003275625],"study_design_scores_gemma":[0.00004104436,0.000002334182,0.006440948,0.000170441,0.000009252115,0.00001481185,0.0001302593,0.00008728601,0.0001175625,0.0003242762,0.9926399,0.00002181189],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005121374,0.0000299926,0.00002553275,0.00001950156,0.00001174562,0.000003876453,0.9980541,0.0001243321,0.001679528],"genre_scores_gemma":[0.0004444337,0.0001268454,0.0001931859,0.00003026892,0.000003663369,0.00003803509,0.9924533,0.0001463715,0.006563892],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2525778,"threshold_uncertainty_score":0.7887626,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01340017801061268,"score_gpt":0.2524788636410853,"score_spread":0.2390786856304726,"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."}}