{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00004103497,0.0002857375,0.0002827397,0.0001560633,0.00005575017,0.00004415081,0.00181997,0.0002864121,0.3459393],"category_scores_gemma":[0.0009718664,0.0003101434,0.0000635333,0.0001662202,0.000002743813,0.00007094494,0.0009051705,0.0005283895,0.0005292109],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005830863,"about_ca_system_score_gemma":0.00003022467,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003064176,"about_ca_topic_score_gemma":0.00001100153,"domain_scores_codex":[0.9990175,0.00000434825,0.0001969596,0.0003344489,0.0001542521,0.000292441],"domain_scores_gemma":[0.9979368,0.0001322617,0.00003597552,0.001831297,0.00002188355,0.000041716],"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":[9.737065e-7,0.000006070853,1.693569e-8,0.001051971,0.00004118192,0.00001322703,9.11424e-7,0.001934006,4.122205e-7,3.449925e-7,0.9953689,0.001582014],"study_design_scores_gemma":[0.00009588937,0.00001644365,4.397687e-7,0.000259973,0.00002600861,0.000006462642,0.000003896932,0.006061244,0.00002347449,0.000005898712,0.9931497,0.0003505445],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[8.054368e-8,0.002134838,0.00001536263,0.00001754089,0.0004514733,0.0002929626,0.9957439,0.001283997,0.00005983184],"genre_scores_gemma":[0.00000277724,0.00007659088,0.0001682212,0.00002031924,0.0002795241,0.0006747554,0.9986047,0.00007206751,0.000101038],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3454101,"threshold_uncertainty_score":0.9999351,"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."}}