{"id":"W2775609832","doi":"10.5061/dryad.c9b25/10","title":"Bayenv output file","year":2015,"lang":"en","type":"dataset","venue":"DRYAD","topic":"Invertebrate Taxonomy and Ecology","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Seasonality; Precipitation; Environmental science; Radar; Quarter (Canadian coin); Metric (unit); Statistics; Mathematics; Geography; Meteorology; Computer science; Engineering; Archaeology; Operations management","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001375367,0.0001855397,0.0002566536,0.00001010376,0.0001135337,0.00004182392,0.0004335728,0.0004101745,0.07395823],"category_scores_gemma":[0.00006950197,0.00006366292,0.00008386258,0.0001112801,0.00005229715,0.00005093541,0.0001459744,0.0002478438,0.01114596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003210113,"about_ca_system_score_gemma":0.00002186304,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001029737,"about_ca_topic_score_gemma":0.007046156,"domain_scores_codex":[0.9990345,0.00005787998,0.0001665052,0.0002943773,0.0001305393,0.0003161625],"domain_scores_gemma":[0.9995342,0.0001000451,0.0001016688,0.00009204332,0.00004971884,0.0001223623],"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":[0.000005431494,0.00003592638,0.000009346545,0.000004809839,0.00001202988,0.00001479658,0.000001985498,1.443662e-7,0.000006667573,0.000001657932,0.9943838,0.005523436],"study_design_scores_gemma":[0.00004527563,0.0001388931,0.0003231615,0.000007531925,0.00001635578,0.000005731331,0.00002260744,0.000003559205,0.000004655074,0.00009769361,0.999127,0.000207559],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003457089,0.00007954955,2.983965e-8,0.000380877,0.0006384103,0.0001229322,0.9957532,0.00003739371,0.0026419],"genre_scores_gemma":[0.00004497953,0.00004296719,0.000009221011,0.001045736,0.0009541308,0.00004281501,0.9932482,4.428743e-7,0.004611544],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06281226,"threshold_uncertainty_score":0.989624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03643873388455061,"score_gpt":0.2130502764114683,"score_spread":0.1766115425269177,"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."}}