{"id":"W6894346808","doi":"10.5683/sp3/w7pcmn","title":"Red Deer (West) Alberta. 1:50,000. Map Sheet 083A05, ed. 1, 1958","year":2022,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Georeference; Raster graphics; General partnership; Aerial photography; Natural (archaeology); Geographic information system; Viewshed analysis; Government (linguistics)","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":[0.0004865153,0.001837261,0.00102619,0.004868282,0.001169645,0.002965375,0.001844427,0.0005278484,0.08964381],"category_scores_gemma":[0.001435998,0.0008062953,0.0005180634,0.01617838,0.0003665974,0.0008188612,0.0008257393,0.001085779,0.08156896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004766058,"about_ca_system_score_gemma":0.008543259,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8311397,"about_ca_topic_score_gemma":0.9069377,"domain_scores_codex":[0.9995034,0.00002077437,0.00003024371,0.0001196316,0.0002072769,0.0001186283],"domain_scores_gemma":[0.9989661,0.00006572191,0.00008481696,0.0001166019,0.0006463408,0.0001203382],"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":[0.00002355932,0.000005481785,0.001085024,0.0001951449,0.00001031632,0.0000141039,0.00003331677,0.00009102513,0.00005267974,0.0002082724,0.9938969,0.004384139],"study_design_scores_gemma":[0.00004950497,0.000004645723,0.01875749,0.0001918003,0.00001489133,0.00003826783,0.0001999595,0.0001298686,0.0001403864,0.0003306036,0.9801229,0.00001978738],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001629124,0.0001083507,0.0000329138,0.00002323843,0.00002241632,0.000006102897,0.9972016,0.0001425722,0.002299882],"genre_scores_gemma":[0.0007128326,0.000146647,0.0002854072,0.00002450652,0.000006157328,0.00002198288,0.9943228,0.00006999938,0.004409668],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1688603,"threshold_uncertainty_score":0.3397095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01579099074073342,"score_gpt":0.2630262091260712,"score_spread":0.2472352183853377,"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."}}