{"id":"W4398629704","doi":"10.7910/dvn/pkjufn/mqwqku","title":"FCC2001.126.ran","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Transport Systems and Technology","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Ran; Biology; Cell biology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00005810544,0.0003749042,0.0004945854,0.0001564948,0.00004241929,0.00003626811,0.000705845,0.0005409308,0.01080566],"category_scores_gemma":[0.00002152627,0.0003959264,0.0001167087,0.0001805404,0.00005178861,0.0001168394,0.00008887835,0.000660095,0.2845771],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005065561,"about_ca_system_score_gemma":0.00002874103,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000178319,"about_ca_topic_score_gemma":0.0002479458,"domain_scores_codex":[0.9987001,0.00001292726,0.0003566683,0.0003707295,0.0001991286,0.0003604371],"domain_scores_gemma":[0.9986229,0.00001978183,0.00005510397,0.001137201,0.00001596694,0.0001490596],"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":[0.000004844879,0.00001131328,0.00000315931,0.0004484207,0.000114442,0.0003993851,0.000008337614,0.00005539726,0.00003540991,0.00003850998,0.9986617,0.0002190675],"study_design_scores_gemma":[0.000264853,0.00002198709,0.00001924233,0.0000676268,0.00009831832,0.00002647375,0.00001529028,0.00006833418,0.00003020683,0.000009194782,0.9989833,0.0003951778],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001036411,0.000005462502,0.0001698303,0.000004447983,0.001391399,0.0002132414,0.9968868,0.0008653384,0.0004530656],"genre_scores_gemma":[0.0001451655,0.0005524524,0.0001531517,0.00008761881,0.0003512847,0.00003185364,0.9985511,0.00005882593,0.00006856515],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2737715,"threshold_uncertainty_score":0.9998493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01028644552546442,"score_gpt":0.1922603851564491,"score_spread":0.1819739396309847,"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."}}