{"id":"W4398328417","doi":"10.7910/dvn/hbikkv/u6xktn","title":"run_b.nc","year":2019,"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":"Seeding; Cloud computing; Turbulence; Meteorology; Environmental science; Cloud condensation nuclei; Atmospheric sciences; Cloud seeding; Computer science; Physics; Aerosol; 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":[0.0002097166,0.0003208801,0.0003597047,0.0001136456,0.0001108025,0.0001248924,0.0008543156,0.0002932963,0.2618807],"category_scores_gemma":[0.0000947982,0.0002682872,0.0001008902,0.0001611134,0.00007146314,0.000349984,0.00007899092,0.0003985415,0.7704147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000577045,"about_ca_system_score_gemma":0.0001486373,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003096303,"about_ca_topic_score_gemma":0.00157533,"domain_scores_codex":[0.9983767,0.00005632043,0.0002216417,0.0005160297,0.0003792584,0.0004500851],"domain_scores_gemma":[0.9984422,0.0001242891,0.0001563887,0.001050729,0.0000308282,0.0001955971],"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":[0.00003117475,0.00001006613,0.0003670576,0.0002812076,0.00003041825,0.0001048651,0.000005531447,0.0002038928,1.972662e-7,0.000001268594,0.9976996,0.001264784],"study_design_scores_gemma":[0.0002125196,0.00009106161,0.001207468,0.00007171493,0.00007335214,0.00002667936,0.00001548333,0.0007242656,0.000001802316,0.00002159703,0.9971883,0.0003657754],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005506911,0.00001026683,0.000007473197,0.000004551982,0.00161774,0.0002310162,0.996343,0.00003315248,0.001697735],"genre_scores_gemma":[0.0001387503,0.0005276359,0.00008243379,0.0007220543,0.0004443147,0.000001201477,0.9970365,0.000006156446,0.001040992],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.508534,"threshold_uncertainty_score":0.9999769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01462436940847789,"score_gpt":0.2173718651715712,"score_spread":0.2027474957630933,"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."}}