{"id":"W4398320257","doi":"10.7910/dvn/hbikkv/n0ksab","title":"RunA.dsd","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Aeolian processes and effects","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Cloud computing; Seeding; Turbulence; Meteorology; Environmental science; Computer science; Physics; Thermodynamics; Operating system","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":[0.0001298112,0.000313172,0.0003473629,0.00007380125,0.0001369042,0.0001413706,0.0008210976,0.0002313028,0.1985677],"category_scores_gemma":[0.0001569031,0.0002690777,0.0000967574,0.0002128093,0.00008249548,0.0002897043,0.00008679379,0.000433966,0.8084534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004414223,"about_ca_system_score_gemma":0.0001396148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002452881,"about_ca_topic_score_gemma":0.001584933,"domain_scores_codex":[0.9984468,0.00005698886,0.0002250931,0.0005188914,0.0003618436,0.0003904011],"domain_scores_gemma":[0.9987633,0.0000904336,0.0001401164,0.0006519749,0.00002514284,0.00032907],"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":[0.00003669522,0.000007832002,0.0001005034,0.0002523972,0.00003247281,0.0003092301,0.000007478025,0.00007255437,2.010901e-7,0.000001359399,0.9976771,0.001502179],"study_design_scores_gemma":[0.0001843454,0.0001013061,0.0005239775,0.0000498438,0.00008167601,0.00002286742,0.00002074711,0.0007343288,0.000002275797,0.00003143135,0.997903,0.0003441643],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00000979724,0.000006343702,0.00001232137,0.00001481577,0.000860778,0.0001715118,0.9977083,0.00005946161,0.00115668],"genre_scores_gemma":[0.00007245012,0.0005126621,0.0001368099,0.001584943,0.0006479825,0.000001370529,0.9968157,0.00000600402,0.0002221167],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6098858,"threshold_uncertainty_score":0.9999762,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01300124575142983,"score_gpt":0.2066156706162821,"score_spread":0.1936144248648522,"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."}}