{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000888258,0.003278472,0.0021682,0.004153703,0.0008227991,0.003758149,0.003747521,0.001897032,0.2292075],"category_scores_gemma":[0.004407746,0.001262254,0.00186316,0.008141614,0.00047876,0.002611218,0.002644759,0.002176737,0.3000923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001193072,"about_ca_system_score_gemma":0.001842114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03071525,"about_ca_topic_score_gemma":0.03830469,"domain_scores_codex":[0.999151,0.0001486173,0.00008447123,0.0003040081,0.0001518401,0.0001600724],"domain_scores_gemma":[0.99853,0.0003166459,0.0001313347,0.0005110247,0.0003077731,0.0002031356],"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":[0.00002707001,0.00000624627,0.0001982927,0.0002433714,0.00002525449,0.00000514523,0.00001229675,0.0001321069,0.00002997155,0.0003989854,0.9980471,0.0008741283],"study_design_scores_gemma":[0.0002101859,0.000009517708,0.001448019,0.0001563486,0.00002699299,0.00001720068,0.0000405473,0.0003290405,0.0001944893,0.001663111,0.9958768,0.00002770909],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003129343,0.00002763873,0.00003749504,0.00002980106,0.00001734753,0.000002722114,0.9983444,0.0008477723,0.0006614726],"genre_scores_gemma":[0.0002819432,0.00004855769,0.0001650186,0.00003508527,0.00000976804,0.00003353833,0.9982311,0.0004904714,0.0007045587],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7707925,"threshold_uncertainty_score":0,"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."}}