{"id":"W149398600","doi":"10.1023/a:1026571515769","title":"Statistical inference on series of atmospheric chemistry data*","year":2000,"lang":"en","type":"article","venue":"Environmental and Ecological Statistics","topic":"Scientific Research and Discoveries","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Series (stratigraphy); Multivariate statistics; Gaussian; Inference; Statistics; Mathematics; Applied mathematics; Computer science; Artificial intelligence; Chemistry; Geology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0000605424,0.00008831303,0.000120779,0.0000011438,0.00009048555,0.00003209548,0.0001396475,0.00002164886,0.06051835],"category_scores_gemma":[0.00001663041,0.00006651602,0.000009609535,0.00002162617,0.0004620826,0.00008366239,0.0001145271,0.00008221326,0.0001346588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009166827,"about_ca_system_score_gemma":0.00001179416,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000180963,"about_ca_topic_score_gemma":0.000001053302,"domain_scores_codex":[0.9992739,0.00002069108,0.0001401041,0.0002300246,0.000157937,0.0001773447],"domain_scores_gemma":[0.9995254,0.0001641941,0.00002826641,0.0001758816,0.000001937569,0.0001043581],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0004184397,0.002332972,0.4045942,0.00006574949,0.0001039886,0.00004595601,0.0001854128,0.0002921415,0.00363441,0.06276973,0.01479869,0.5107583],"study_design_scores_gemma":[0.0007475359,0.0007192446,0.9193037,0.000009893401,0.00002753114,0.000002809194,0.0006747009,0.003892705,0.001610834,0.05148332,0.02115156,0.000376198],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9792534,0.00001500629,0.004339335,0.00002348697,0.00002021094,0.00007352387,0.006219751,0.00000577319,0.01004957],"genre_scores_gemma":[0.9897796,0.00004160311,0.006896432,0.00001649915,0.00002822819,0.000005635289,0.0007812535,0.000003481579,0.0024473],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5147094,"threshold_uncertainty_score":0.9403405,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01570595791643378,"score_gpt":0.2544746757823289,"score_spread":0.2387687178658951,"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."}}