{"id":"W6931666211","doi":"10.5683/sp3/5zzzix","title":"Albas (East) British Columbia. 1:50,000. Map Sheet 082M03, ed. 1, 1961","year":2022,"lang":"en","type":"dataset","venue":"Borealis","topic":"Emergency and Acute Care Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Georeference; General partnership; Raster graphics; Natural (archaeology); Government (linguistics); Geographic information system; Aerial photography; 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":[0.0003630735,0.001802273,0.001297053,0.004740595,0.001542568,0.00369629,0.001487166,0.0006550783,0.154235],"category_scores_gemma":[0.002737257,0.0007776034,0.0005392251,0.02022781,0.0003879152,0.0009971443,0.001036343,0.001239365,0.130016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007864561,"about_ca_system_score_gemma":0.0138873,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9264222,"about_ca_topic_score_gemma":0.9516504,"domain_scores_codex":[0.9994286,0.0000280879,0.00005084966,0.000147014,0.0001937067,0.0001516642],"domain_scores_gemma":[0.9981597,0.00009905013,0.0001186773,0.0001912883,0.00123189,0.000199439],"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":[0.00001758245,0.000003161015,0.0005695612,0.0001795626,0.000007290202,0.00001114702,0.00001539081,0.00004822301,0.00001893932,0.0001484961,0.9961092,0.002871445],"study_design_scores_gemma":[0.00003947377,0.000002626809,0.01399557,0.0002661946,0.00001184424,0.00002513011,0.0001402697,0.0001002469,0.0001026617,0.0001959936,0.9851006,0.00001949973],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008972181,0.00008399841,0.00001692519,0.00003136176,0.00001479722,0.000005334934,0.9970152,0.00009998686,0.002642633],"genre_scores_gemma":[0.0009144081,0.0002473949,0.0001512583,0.0000362139,0.000008227197,0.00004854521,0.9868671,0.0001062044,0.0116206],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.154235,"threshold_uncertainty_score":0.5159674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01293655438147566,"score_gpt":0.2594576763795062,"score_spread":0.2465211219980305,"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."}}