{"id":"W6894459407","doi":"10.5683/sp3/8xobes","title":"Tilley (West) Alberta. 1:50,000. Map Sheet 072L05, ed. 1, 1960","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; Geographic information system; Orthophoto; Aerial photography","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":[0.0005632559,0.00249154,0.001534419,0.005827928,0.001421821,0.004897312,0.002297151,0.0007701886,0.1381093],"category_scores_gemma":[0.002360801,0.001033882,0.0007222996,0.02085948,0.0004813782,0.001339516,0.001226324,0.001476953,0.1405516],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00613108,"about_ca_system_score_gemma":0.01299788,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8309925,"about_ca_topic_score_gemma":0.8997833,"domain_scores_codex":[0.9992871,0.0000329055,0.00004458768,0.0001986641,0.0002738066,0.0001631009],"domain_scores_gemma":[0.9985299,0.0001122616,0.0001098987,0.0001963389,0.000848815,0.0002027627],"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":[0.00001825906,0.000003958175,0.0004774926,0.0002079178,0.000009095953,0.00001132601,0.00002399282,0.00008669264,0.0000357615,0.0002652792,0.9957617,0.003098447],"study_design_scores_gemma":[0.00003509235,0.000003009546,0.005972576,0.0001815104,0.00001096877,0.00002223075,0.0001101131,0.00009300503,0.00009545933,0.0003741248,0.9930842,0.00001769941],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007548893,0.0001110996,0.00003617183,0.00002714517,0.00002091829,0.000004404043,0.9970616,0.0002082389,0.002454982],"genre_scores_gemma":[0.0003956902,0.0001523757,0.0002360242,0.00002491863,0.000006437842,0.0000166869,0.9948317,0.0001276964,0.004208497],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1690075,"threshold_uncertainty_score":0.4620217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01491715089153205,"score_gpt":0.2623397745418465,"score_spread":0.2474226236503145,"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."}}