{"id":"W6969369127","doi":"10.5683/sp2/26s6gm","title":"Bonehouse -- Herschel Island -- Laser Scanning -- Metadata -- 20818/19","year":2021,"lang":"en","type":"dataset","venue":"Borealis","topic":"Agricultural Economics and Policy","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Laser scanning; Metadata; Rest (music); Scanner; Point cloud; Data set","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":[0.000704639,0.001982347,0.001057835,0.002587984,0.0007922069,0.00175534,0.002360116,0.001374034,0.03887583],"category_scores_gemma":[0.002225144,0.0006426426,0.0008787811,0.004381249,0.0005262588,0.001221369,0.002185912,0.001476117,0.09885658],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00107524,"about_ca_system_score_gemma":0.002208862,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05650638,"about_ca_topic_score_gemma":0.1159512,"domain_scores_codex":[0.9991989,0.00007162107,0.00006009248,0.0002242591,0.0002870244,0.000158151],"domain_scores_gemma":[0.9989452,0.0001296098,0.00009936243,0.0003252443,0.0003577817,0.0001429316],"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":[0.00007823099,0.00003995774,0.002613517,0.0004330683,0.00003137525,0.00004706718,0.00006644661,0.0004455477,0.0004859612,0.0005113113,0.9894308,0.005816768],"study_design_scores_gemma":[0.00007406612,0.00001826,0.0111702,0.0001736584,0.00001703933,0.00006986879,0.0001993606,0.0006645988,0.001141565,0.000705348,0.9857236,0.00004238953],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003872763,0.00003863619,0.0001158305,0.00002762927,0.00002012827,0.00001101377,0.9977887,0.0006612368,0.0009495782],"genre_scores_gemma":[0.0004169424,0.00001911215,0.0002859108,0.0000107817,0.000002746537,0.00002622201,0.9987158,0.00008256075,0.0004400715],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9434936,"threshold_uncertainty_score":0.1300527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02770523234157651,"score_gpt":0.2409681226205015,"score_spread":0.213262890278925,"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."}}