{"id":"W6913220210","doi":"10.5683/sp3/o5decd","title":"[Untitled] (East) Alberta. 1:50,000. Map Sheet 084D06, ed. 1, 1962","year":2022,"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); Digital mapping; Aerial photography; Geographic information system; Government (linguistics); 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":[0.0005026957,0.002273049,0.001333173,0.005476012,0.001258053,0.004054956,0.002299689,0.000753088,0.1895597],"category_scores_gemma":[0.002488616,0.0009712828,0.000703616,0.02146139,0.0005049119,0.001330219,0.001300043,0.001424006,0.1916861],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005661465,"about_ca_system_score_gemma":0.01159906,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.808348,"about_ca_topic_score_gemma":0.8843082,"domain_scores_codex":[0.9993563,0.00002973225,0.00003795408,0.0001564262,0.0002739258,0.0001456558],"domain_scores_gemma":[0.9983339,0.0001072026,0.0001074668,0.0002123481,0.001051453,0.000187619],"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":[0.00001516409,0.000003558668,0.000369988,0.0001760357,0.00000727239,0.000008151692,0.00002170664,0.00007958861,0.00003226274,0.0002055749,0.996436,0.002644705],"study_design_scores_gemma":[0.00003556084,0.000002716081,0.005359343,0.0001417407,0.000008936682,0.00001889834,0.0001027472,0.00008331329,0.0001019682,0.0003252687,0.9938014,0.0000181047],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005808737,0.00007415323,0.00003741047,0.00002342331,0.00002599201,0.000005800685,0.9965506,0.0002173959,0.003007148],"genre_scores_gemma":[0.0004140817,0.0001204967,0.0002689838,0.00002609333,0.000006816062,0.00002329992,0.9937201,0.0001517334,0.005268444],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.191652,"threshold_uncertainty_score":0.6341404,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01381611877131391,"score_gpt":0.2549065731554944,"score_spread":0.2410904543841804,"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."}}