{"id":"W6950502878","doi":"10.5683/sp3/lyakyg","title":"Coniston Ontario. 1:50,000. Map Sheet 041I07, ed. 6, 1995","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); Aerial photography; Digital mapping; Government (linguistics); Orthophoto; 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":[0.0004261945,0.00163083,0.001191074,0.004873759,0.001410226,0.002502055,0.001698469,0.0005441754,0.1529728],"category_scores_gemma":[0.002575678,0.0009279935,0.0004991257,0.02079406,0.000410875,0.001033937,0.0009185742,0.0008039427,0.110752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01016333,"about_ca_system_score_gemma":0.0152059,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9146698,"about_ca_topic_score_gemma":0.9528022,"domain_scores_codex":[0.9993742,0.00002686123,0.00004708111,0.0001390247,0.0002724985,0.0001404575],"domain_scores_gemma":[0.998026,0.0001277933,0.0001875096,0.0002129652,0.001241674,0.0002040778],"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":[0.00001319284,0.000002857812,0.0007184785,0.0001948829,0.000005897043,0.00001052746,0.00003253796,0.00006001438,0.00002866698,0.0001820351,0.9950476,0.003703336],"study_design_scores_gemma":[0.00002299928,0.000002273262,0.01101449,0.0001279505,0.000007709518,0.00001696294,0.0001229215,0.00007679802,0.00007987993,0.0001406887,0.9883754,0.00001193724],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008723159,0.00005888296,0.00002562494,0.00002929814,0.000009491298,0.000006163238,0.9968454,0.00007662023,0.002861141],"genre_scores_gemma":[0.0007766258,0.0001968392,0.0002355897,0.00002399317,0.000005644764,0.00005238775,0.9883003,0.00008145833,0.01032713],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1529728,"threshold_uncertainty_score":0.5117451,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01747972763392456,"score_gpt":0.2599357742410083,"score_spread":0.2424560466070838,"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."}}