{"id":"W4398280876","doi":"10.7910/dvn/hbikkv/5wr3uv","title":"RunD3.coldat","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Seeding; Cloud computing; Turbulence; Environmental science; Meteorology; Mechanics; 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":[0.0001057893,0.0003606178,0.0003376864,0.000001508883,0.0001484526,0.0000797652,0.001099213,0.0002569768,0.3669852],"category_scores_gemma":[0.00007464728,0.0003364399,0.0001218937,0.0002068186,0.0002209786,0.0002296459,0.001709833,0.0004283515,0.8313079],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001583257,"about_ca_system_score_gemma":0.00003205302,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00115328,"about_ca_topic_score_gemma":0.0002499247,"domain_scores_codex":[0.9980429,0.00004872547,0.0002810504,0.0007085859,0.0005224393,0.0003962415],"domain_scores_gemma":[0.998301,0.00002801305,0.0001714299,0.001192582,0.000003978398,0.0003029999],"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":[0.00001744094,0.00004891795,0.00007671492,0.000021695,0.00002185388,0.0001465228,0.00001224231,0.00002069698,0.00003303586,0.000003628423,0.9992783,0.0003189253],"study_design_scores_gemma":[0.0002158191,0.00005617394,0.0002210303,0.00001492476,0.00008030473,0.000009010336,0.00002942533,0.00003623448,0.00000849345,0.00001317459,0.9989156,0.0003998586],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004665658,3.833881e-7,0.00005035623,0.00001641772,0.0004549175,0.0002325877,0.9971365,0.00006047254,0.002001728],"genre_scores_gemma":[0.00002378526,0.0001941518,0.0007647579,0.002150837,0.0002547253,0.00002183445,0.9954828,0.00002738435,0.001079748],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4643228,"threshold_uncertainty_score":0.9999087,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01027735251325762,"score_gpt":0.2105026389570718,"score_spread":0.2002252864438142,"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."}}