{"id":"W6931635746","doi":"10.5683/sp3/a1zw0l","title":"Fort Coulonge (West) Ontario. 1:50,000. Map Sheet 031F15, ed. 1, 1956","year":2021,"lang":"en","type":"dataset","venue":"Borealis","topic":"South Asian Studies and Diaspora","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Georeference; General partnership; Raster graphics; Natural (archaeology); Viewshed analysis; Aerial photography; Digital mapping","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":[0.0004160786,0.001631789,0.001080589,0.004356264,0.00186953,0.003157222,0.00137984,0.0005197429,0.1947161],"category_scores_gemma":[0.002475483,0.0006762471,0.0005633424,0.0203938,0.0004615176,0.001121552,0.0009560962,0.0008801637,0.1127855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01454365,"about_ca_system_score_gemma":0.02080873,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9777465,"about_ca_topic_score_gemma":0.9864522,"domain_scores_codex":[0.99937,0.00002423226,0.00003899565,0.0001391811,0.00025175,0.0001758912],"domain_scores_gemma":[0.9979818,0.00008017776,0.000134833,0.0001715883,0.001421579,0.0002100729],"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":[0.00002212929,0.0000034463,0.001141356,0.0002118883,0.00000806119,0.00001438499,0.00005368254,0.00006558569,0.00002731285,0.0002871358,0.9926643,0.005500697],"study_design_scores_gemma":[0.00002530146,0.000002912454,0.01653322,0.0001681497,0.000007092612,0.00002014813,0.0001870397,0.00005754538,0.0000731238,0.0001301094,0.9827816,0.0000137142],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001518051,0.0001260772,0.00003356469,0.00004478009,0.0000183912,0.000009620838,0.9943573,0.0001059117,0.005152555],"genre_scores_gemma":[0.0023173,0.0004480176,0.0003243796,0.00005370991,0.00001319628,0.00007051536,0.9687343,0.0001587251,0.0278799],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1947161,"threshold_uncertainty_score":0.6513903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02804444193362087,"score_gpt":0.2389512546368699,"score_spread":0.210906812703249,"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."}}