{"id":"W4398476710","doi":"10.7910/dvn/hbikkv/wfpgbj","title":"RunD1.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":"Seeding; Cloud computing; Turbulence; Environmental science; Cloud seeding; Meteorology; Atmospheric sciences; Materials 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":[0.0001326081,0.0003172014,0.000352177,0.00007492797,0.0001428158,0.0001518895,0.0008247075,0.0002357581,0.1955289],"category_scores_gemma":[0.000157345,0.0002733351,0.0001008372,0.0002142569,0.0000855078,0.0003000539,0.00008857607,0.0004396658,0.8133801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004779488,"about_ca_system_score_gemma":0.0001455625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002621644,"about_ca_topic_score_gemma":0.00190557,"domain_scores_codex":[0.9984159,0.00005755901,0.0002299197,0.0005334166,0.0003659217,0.0003972445],"domain_scores_gemma":[0.9987347,0.00009273008,0.0001445428,0.0006683592,0.00002502856,0.0003347002],"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":[0.0000387092,0.000008203087,0.00009966923,0.0002553794,0.00003304565,0.0003096545,0.000007594357,0.00007447592,2.084688e-7,0.000001745219,0.9979349,0.001236362],"study_design_scores_gemma":[0.0001873854,0.0001049944,0.0004475048,0.00005102716,0.00008370313,0.00002391076,0.0000213111,0.0007509056,0.000002070475,0.00004164132,0.9979359,0.0003496507],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00000995893,0.000006295199,0.00001287556,0.00001535568,0.0008710956,0.0001759135,0.9974906,0.00006087557,0.001357071],"genre_scores_gemma":[0.00007687842,0.0005081129,0.0001419587,0.001647086,0.0006701108,0.000001283196,0.9967194,0.000006160132,0.0002290254],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6178511,"threshold_uncertainty_score":0.9999719,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01350146037883882,"score_gpt":0.2076373277425862,"score_spread":0.1941358673637474,"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."}}