{"id":"W4394342404","doi":"10.6084/m9.figshare.21443805","title":"Input data for Atollgen pipeline","year":2022,"lang":"en","type":"dataset","venue":"Figshare","topic":"Offshore Engineering and Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fonds de recherche du Québec – Nature et technologies","keywords":"Pipeline (software); Computer science; Database; Operating system","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001162631,0.002546072,0.001164054,0.0033084,0.001173851,0.002371627,0.00267912,0.001974228,0.1259907],"category_scores_gemma":[0.005674036,0.0007738596,0.001390827,0.005429886,0.0003889185,0.001546822,0.002247384,0.001691951,0.1951697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001736724,"about_ca_system_score_gemma":0.002309315,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01968116,"about_ca_topic_score_gemma":0.03197792,"domain_scores_codex":[0.9987562,0.0001854971,0.0001252501,0.0004369421,0.0003070096,0.0001890616],"domain_scores_gemma":[0.9978046,0.0005615244,0.0001463959,0.000626375,0.0006698517,0.0001912434],"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":[0.00008479087,0.00001737503,0.0007214,0.000355797,0.00001570045,0.00001695088,0.00002043395,0.0002682497,0.0001957743,0.0003006788,0.9956272,0.002375669],"study_design_scores_gemma":[0.0001444321,0.00002194267,0.002721209,0.0001618252,0.00002250498,0.00004101424,0.0001031531,0.0004402702,0.0006479588,0.001022367,0.9946433,0.00002995885],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001688445,0.00004095654,0.0001038265,0.00006672351,0.00002400702,0.00001662242,0.9976708,0.0009645739,0.0009436568],"genre_scores_gemma":[0.0003651185,0.00002903754,0.0003950454,0.00005093993,0.000005869984,0.00007980053,0.9981511,0.0002086234,0.0007144632],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1259907,"threshold_uncertainty_score":0.4214807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05676803768223371,"score_gpt":0.2608274665483923,"score_spread":0.2040594288661586,"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."}}