{"id":"W6931940104","doi":"10.5683/sp2/baozeb","title":"Glenbow General Store and Post Office -- Glenbow -- Laser Scanning -- Metadata -- 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":"Metadata; Post office; Laser scanning; Laser","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":[0.001112106,0.002761476,0.001279437,0.004237535,0.0009434376,0.002213947,0.002655871,0.001893045,0.03497114],"category_scores_gemma":[0.005820354,0.000756881,0.001187413,0.006471137,0.0007650622,0.001863567,0.002231041,0.001590099,0.09140126],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001797248,"about_ca_system_score_gemma":0.004684668,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07961883,"about_ca_topic_score_gemma":0.182195,"domain_scores_codex":[0.9985271,0.0001091798,0.0001203627,0.00037665,0.0005521101,0.0003146305],"domain_scores_gemma":[0.9969665,0.000402594,0.0002788645,0.0008401886,0.001214082,0.0002978839],"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":[0.00007237284,0.00001759219,0.001327795,0.0002524288,0.00001581245,0.00001985799,0.00002923943,0.0001688823,0.0002156181,0.0002611488,0.9945063,0.003112874],"study_design_scores_gemma":[0.0001350851,0.00002141582,0.01101932,0.000281165,0.00003272962,0.00009803293,0.0002094077,0.0004954967,0.001148137,0.001267615,0.9852425,0.00004916053],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002802549,0.000059807,0.0001088756,0.00005414647,0.0000378474,0.00001111318,0.9975734,0.0009149054,0.0009595192],"genre_scores_gemma":[0.0004338404,0.00004341727,0.0002431704,0.00002307328,0.000008354604,0.00003074723,0.9983274,0.0000866173,0.0008033678],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07961883,"threshold_uncertainty_score":0.1583108,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02818748042988821,"score_gpt":0.2874599339697347,"score_spread":0.2592724535398465,"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."}}