{"id":"W6969179250","doi":"10.5683/sp2/sikjdj","title":"Small House No.11 -- Herschel Island -- Laser Scanning -- Metadata -- 2019","year":2021,"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; Data set; Set (abstract data type); Laser scanning","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":[0.0008257349,0.00208715,0.001406895,0.002259112,0.0009546243,0.001807655,0.002453035,0.001294212,0.03253689],"category_scores_gemma":[0.002011487,0.0006470812,0.0008849031,0.003985509,0.000690633,0.001209659,0.001754146,0.001135149,0.08358046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00130683,"about_ca_system_score_gemma":0.002103959,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06559141,"about_ca_topic_score_gemma":0.1695029,"domain_scores_codex":[0.99886,0.00009678281,0.0000740416,0.0003737063,0.0003921929,0.0002032544],"domain_scores_gemma":[0.998743,0.000121587,0.0001111752,0.0004315565,0.0004166786,0.0001760179],"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":[0.0001345019,0.00003824243,0.003290432,0.0004604588,0.00004807996,0.00007512653,0.00008764345,0.0004853575,0.001107286,0.0004607314,0.9848694,0.008942766],"study_design_scores_gemma":[0.00006389516,0.00002573618,0.01716319,0.0001362018,0.00003185924,0.0001362989,0.0001995131,0.000584584,0.002185702,0.0009115629,0.9784892,0.0000723884],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0009977183,0.0001044488,0.0004135793,0.00004302966,0.00004417435,0.00002380515,0.9943479,0.001677162,0.002348215],"genre_scores_gemma":[0.001049871,0.00003087723,0.0005624861,0.00001626092,0.000005683409,0.00003686045,0.9972941,0.0001614964,0.0008423412],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9344086,"threshold_uncertainty_score":0.1304192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03517363679366028,"score_gpt":0.2674241248628982,"score_spread":0.232250488069238,"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."}}