{"id":"W6912826494","doi":"10.5683/sp2/vicsum","title":"Cochrane Ranche -- Cochrane -- Laser Scanning -- Metadata -- July -- 2020","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; Laser scanning; Laser; Intersection (aeronautics); Data set","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001080982,0.001435527,0.0012004,0.003951678,0.0009247754,0.002602175,0.002081502,0.001296069,0.03148354],"category_scores_gemma":[0.005029583,0.0006261772,0.0007918899,0.007374526,0.0006136926,0.001103939,0.001788985,0.001069476,0.05112049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001816541,"about_ca_system_score_gemma":0.004323711,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1057272,"about_ca_topic_score_gemma":0.2309635,"domain_scores_codex":[0.9987956,0.0001200437,0.0001141548,0.0003352128,0.0004362951,0.0001986016],"domain_scores_gemma":[0.9976356,0.0003729194,0.0002639052,0.0005500376,0.0009905588,0.000186942],"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":[0.0001090084,0.00001944012,0.003116671,0.0007607082,0.00003864,0.00004699158,0.00007470448,0.0004346571,0.000444942,0.0008622452,0.9880404,0.006051663],"study_design_scores_gemma":[0.00004110964,0.000009098155,0.009194127,0.0002372812,0.00001638638,0.00005455354,0.0001211691,0.0002060943,0.0005357969,0.0005222374,0.9890305,0.00003162461],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002767187,0.00008331278,0.00009946028,0.00002609958,0.00001835071,0.000009074268,0.9981436,0.0003230846,0.001020342],"genre_scores_gemma":[0.000602005,0.00004510408,0.0003609273,0.0000164966,0.000004416119,0.000035211,0.9982721,0.00008310004,0.0005805793],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8942728,"threshold_uncertainty_score":0.2102237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02261212988581213,"score_gpt":0.3055834952909408,"score_spread":0.2829713654051287,"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."}}