{"id":"W6950677063","doi":"10.5683/sp3/i6s6bn","title":"Sharbot Lake Ontario. 1:50,000. Map Sheet 031C15, ed. 5, 1994","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; Natural (archaeology); Raster graphics; Topographic map (neuroanatomy); Aerial photography; Viewshed analysis; Geographic information system","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":[0.0004188464,0.001927283,0.001340117,0.005840731,0.001545727,0.002712699,0.001977791,0.0005890642,0.1437794],"category_scores_gemma":[0.002467307,0.001019354,0.0005892939,0.02393848,0.0004620899,0.001091844,0.001076229,0.0009056876,0.103314],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009898942,"about_ca_system_score_gemma":0.0155779,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8942004,"about_ca_topic_score_gemma":0.9413055,"domain_scores_codex":[0.9993242,0.00002679552,0.00005219837,0.0001442028,0.0003008287,0.000151864],"domain_scores_gemma":[0.9981825,0.0001086855,0.0001811409,0.0002026095,0.001126348,0.0001987415],"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":[0.00001490187,0.000003847401,0.0007346733,0.0002472495,0.000007940693,0.00001097318,0.00003943949,0.00006567599,0.00003554512,0.0001810057,0.9953222,0.003336624],"study_design_scores_gemma":[0.00003451249,0.000003266759,0.0134737,0.0001302342,0.00001070341,0.00001912786,0.0001347894,0.00009368244,0.00008603519,0.0001681707,0.9858305,0.00001524023],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008086972,0.0000399318,0.0000231543,0.00002223275,0.000007749501,0.000005374654,0.9980216,0.00008172037,0.001717259],"genre_scores_gemma":[0.0005028817,0.0001112144,0.0001646309,0.00001424183,0.000003965622,0.00004549134,0.9943276,0.0000653878,0.004764531],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1437794,"threshold_uncertainty_score":0.48099,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01871586278815374,"score_gpt":0.2559666985197921,"score_spread":0.2372508357316384,"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."}}