{"id":"W6950300028","doi":"10.5683/sp/vwdobl","title":"Perrenoud Homestead -- Cochrane -- Laser Scanning -- June 2017","year":2018,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Laser scanning; Laser; Scanner; Data set; Software; Process (computing)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001985176,0.003149042,0.001893531,0.003428043,0.001013157,0.002835622,0.004011414,0.002746596,0.04801561],"category_scores_gemma":[0.01086845,0.0007903192,0.001697583,0.004396935,0.0007755137,0.001695376,0.002640467,0.001646542,0.1051272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001901568,"about_ca_system_score_gemma":0.002981862,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03411607,"about_ca_topic_score_gemma":0.08532837,"domain_scores_codex":[0.9981217,0.0003726335,0.0001755591,0.0005782634,0.0005064431,0.0002455022],"domain_scores_gemma":[0.9962499,0.0009261905,0.0003861325,0.001080946,0.001059342,0.0002975165],"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":[0.000168683,0.00002427543,0.001100153,0.0005859813,0.00004124631,0.00003100002,0.00002328968,0.0002278682,0.00008355243,0.0002451175,0.9936302,0.003838514],"study_design_scores_gemma":[0.000258411,0.00004460288,0.006479459,0.0004922216,0.00006397152,0.000198603,0.0001096775,0.000569054,0.0007401464,0.001270731,0.989715,0.00005804943],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005260542,0.0004644897,0.0002463724,0.0001268505,0.00007909351,0.000032696,0.995259,0.001416716,0.001848657],"genre_scores_gemma":[0.0009537821,0.0001152505,0.0005325883,0.00005995977,0.00002034579,0.00008785084,0.996901,0.0001963266,0.001132773],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9658839,"threshold_uncertainty_score":0.1606283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02669035877706318,"score_gpt":0.3134785240854877,"score_spread":0.2867881653084245,"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."}}