{"id":"W6913145385","doi":"10.5683/sp3/qgwsnb","title":"Three Hills Alberta. 1:50,000. Map Sheet 082P11, ed. 1, 1967","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); Aerial photography; Topographic map (neuroanatomy); Viewshed analysis; Orthophoto; Geographic information system","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":[0.0005628563,0.002307447,0.001429742,0.006028112,0.001484362,0.004059673,0.00227622,0.0007106403,0.1193726],"category_scores_gemma":[0.002366489,0.0009968408,0.0006841789,0.02363919,0.000458759,0.001150362,0.001070196,0.001487654,0.1087498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007145911,"about_ca_system_score_gemma":0.0147028,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8746953,"about_ca_topic_score_gemma":0.9241647,"domain_scores_codex":[0.9993122,0.00003111921,0.00004507475,0.0001571007,0.0003012634,0.0001533457],"domain_scores_gemma":[0.9983625,0.000117619,0.0001184636,0.0001833802,0.001016706,0.0002013991],"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":[0.00001849062,0.000004464598,0.0005749327,0.0001989623,0.00000844606,0.00001291195,0.00002618813,0.00009544767,0.00003171261,0.000283298,0.9958876,0.002857553],"study_design_scores_gemma":[0.00004008148,0.000003231358,0.00867444,0.0001914587,0.00001219433,0.00002574307,0.0001589707,0.0001233162,0.0001015589,0.0004144479,0.9902343,0.00002029449],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007185776,0.00007834686,0.00002834741,0.00002792033,0.00001863057,0.000004055604,0.9975579,0.0001282886,0.002084616],"genre_scores_gemma":[0.000448202,0.0001500767,0.0002456101,0.0000234343,0.000006322595,0.00002050958,0.9945613,0.000096499,0.004448086],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1253047,"threshold_uncertainty_score":0.399341,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0154471278439318,"score_gpt":0.2561427435269131,"score_spread":0.2406956156829813,"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."}}