{"id":"W6913200367","doi":"10.5683/sp2/e7mtlk","title":"Glenbow General Store and Post Office -- Glenbow -- Laser Scanning -- 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; Documentation; Scanner; Post office","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":[0.0009339623,0.00389973,0.001926706,0.00311364,0.001043457,0.002188337,0.003551163,0.002541528,0.03281714],"category_scores_gemma":[0.003093757,0.0007322723,0.001393359,0.00438876,0.0007441315,0.00149325,0.00250949,0.001478319,0.09679738],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001487036,"about_ca_system_score_gemma":0.002712717,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03602229,"about_ca_topic_score_gemma":0.1056088,"domain_scores_codex":[0.9984115,0.0001490537,0.0001123496,0.0004787713,0.0005501789,0.0002980399],"domain_scores_gemma":[0.9986822,0.0001717192,0.0001003553,0.000409327,0.0005103184,0.0001259902],"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":[0.0001145637,0.0000354487,0.001185952,0.0003930475,0.00002901321,0.00005516072,0.00002945759,0.0003105249,0.0003561682,0.0002163218,0.9893242,0.007950204],"study_design_scores_gemma":[0.0001200334,0.00003982081,0.01049928,0.0004196424,0.00004580847,0.0003579024,0.0002180526,0.001378868,0.002158108,0.001418698,0.9832652,0.00007874548],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001279957,0.0004288149,0.00052398,0.0001163568,0.0001286943,0.00003519036,0.9912253,0.003303545,0.002958246],"genre_scores_gemma":[0.001115649,0.0001153409,0.0005907498,0.00003509407,0.00001593316,0.00004888009,0.9967223,0.0001806062,0.001175485],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9639777,"threshold_uncertainty_score":0.1097843,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02078534901544284,"score_gpt":0.2790752595622762,"score_spread":0.2582899105468334,"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."}}