{"id":"W6944999233","doi":"10.18739/a23r0pt92","title":"Cloud microphysical properties at Arctic atmospheric observatories: Eureka, Canada","year":2016,"lang":"en","type":"dataset","venue":"California Digital Library","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cloud computing; Cloud top; Arctic; Liquid water content; Data set; The arctic; Atmospheric research; Cloud fraction","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"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":[0.00002627155,0.0007288074,0.0005944544,5.430197e-7,0.0002661015,0.0002963478,0.001112399,0.0003026905,0.01187161],"category_scores_gemma":[0.00005602153,0.0004980423,0.0002043341,0.0002930599,0.0005919402,0.0007095471,0.001992877,0.0003688399,0.009961138],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007500247,"about_ca_system_score_gemma":0.0004188562,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02218984,"about_ca_topic_score_gemma":0.008537947,"domain_scores_codex":[0.9969623,0.00004567218,0.0005369361,0.0008937361,0.0007359046,0.0008254374],"domain_scores_gemma":[0.9982037,0.00007685898,0.0002674554,0.0009307227,0.000009230777,0.0005120188],"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":[0.00008483132,0.00007487383,0.009638238,0.0001028825,0.00004111817,0.000135185,0.000004284895,0.00001233126,0.00002059417,0.000001066347,0.989263,0.0006215922],"study_design_scores_gemma":[0.0001976944,0.00007842304,0.0003368626,0.0001198897,0.00003470699,0.00002296999,0.00001411033,0.00001009136,0.0001373192,0.00008198274,0.998176,0.0007899831],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.03514938,0.0002966217,0.000003252066,0.0005334347,0.0006756617,0.0003276433,0.9618963,0.0001014384,0.001016271],"genre_scores_gemma":[0.01042575,0.0001777536,0.0000911202,0.00305662,0.001167409,0.00009146459,0.9649221,0.0001757316,0.01989209],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02472362,"threshold_uncertainty_score":0.9997471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005683342112682633,"score_gpt":0.1538684611538913,"score_spread":0.1481851190412087,"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."}}