{"id":"W6894212273","doi":"10.5683/sp3/apqhxv","title":"Wekweyaukastik Rapids Ontario. 1:50,000. Map Sheet 042I07, ed. 2, 1986","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); Government (linguistics); Aerial photography; 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":[0.0004985392,0.001785194,0.001324803,0.005400165,0.001440141,0.002759038,0.001668574,0.0005205351,0.1026501],"category_scores_gemma":[0.002757334,0.001039872,0.0006191581,0.02067468,0.0004765102,0.001151544,0.001038605,0.001012256,0.09115434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01027537,"about_ca_system_score_gemma":0.01775461,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9169791,"about_ca_topic_score_gemma":0.954272,"domain_scores_codex":[0.9992905,0.00003052783,0.00005517973,0.0001518671,0.0003106317,0.000161299],"domain_scores_gemma":[0.9979581,0.0001158937,0.0002071109,0.0002369753,0.001267512,0.0002144472],"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":[0.00002027068,0.000004104962,0.0009782327,0.000308164,0.000009081609,0.00001309318,0.00005768932,0.00008656047,0.0000482015,0.0002691804,0.9942909,0.003914508],"study_design_scores_gemma":[0.00002451749,0.000002804192,0.01175213,0.0001321367,0.000008700677,0.00001673407,0.0001328696,0.00007433263,0.00009527029,0.0001408437,0.9876057,0.00001401286],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009104718,0.00005595635,0.00002857096,0.00002513597,0.000009490392,0.000005101815,0.9976841,0.00009956185,0.002001044],"genre_scores_gemma":[0.0006312534,0.0001463978,0.000224595,0.00001414403,0.000004265179,0.00003864328,0.9929194,0.00009020093,0.005931186],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1026501,"threshold_uncertainty_score":0.3433987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01690734634007192,"score_gpt":0.2541527095224831,"score_spread":0.2372453631824112,"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."}}