{"id":"W6931685384","doi":"10.5683/sp3/em13pl","title":"Wolseley (West) Saskatchewan. 1:50,000. Map Sheet 062L06, ed. 1, 1967","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; Raster graphics; Natural (archaeology); Digital mapping; Geographic information system; Aerial photography; Orthophoto; Government (linguistics)","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":[0.0004340126,0.001784809,0.001093453,0.004005538,0.000865724,0.003261082,0.001496632,0.0005632266,0.2316725],"category_scores_gemma":[0.002231299,0.001034015,0.000607382,0.01973699,0.0003352114,0.001577925,0.001313272,0.001138452,0.2348119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004417709,"about_ca_system_score_gemma":0.01047903,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7065497,"about_ca_topic_score_gemma":0.8175068,"domain_scores_codex":[0.9995017,0.00003864993,0.00005009506,0.0001504295,0.0001378301,0.0001212466],"domain_scores_gemma":[0.9985037,0.0001047911,0.0001101403,0.0002922729,0.0008408752,0.0001483662],"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":[0.00002957402,0.000004197669,0.0008836297,0.0002288613,0.00001675101,0.00001794229,0.00003408021,0.0001079387,0.0000729086,0.0003359304,0.9923488,0.005919321],"study_design_scores_gemma":[0.00003044699,0.000002383005,0.008074404,0.0001968573,0.000008995367,0.00001581091,0.0001651551,0.00005936348,0.0001375074,0.0003066319,0.9909842,0.00001822922],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001018343,0.00004773247,0.00003893731,0.00002244748,0.00001568751,0.000004697186,0.9967667,0.0001282341,0.002873733],"genre_scores_gemma":[0.000808481,0.0001847471,0.0002348167,0.00003540526,0.000004253733,0.00004393621,0.9860303,0.0001699606,0.01248806],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2934503,"threshold_uncertainty_score":0.7750216,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01494786091815851,"score_gpt":0.260120809673409,"score_spread":0.2451729487552505,"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."}}