{"id":"W4394127803","doi":"10.6084/m9.figshare.3517967","title":"Appendix E. Model selection summary regarding Diptera abundance and biomass measured on 40 farms located in southeastern Quebec, Canada, for three years separately (2006, 2007, and 2008).","year":2016,"lang":"en","type":"dataset","venue":"Figshare","topic":"Forensic Entomology and Diptera Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Selection (genetic algorithm); Abundance (ecology); Geography; Biomass (ecology); Ecology; Forestry; Archaeology; Biology; Computer science; Artificial intelligence","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":[],"category_scores_codex":[0.00007747893,0.0002921084,0.0003480959,0.00003594856,0.0001742568,0.00006113732,0.0001692768,0.0002940063,0.001447339],"category_scores_gemma":[0.0001311182,0.000131368,0.00004292982,0.0001108191,0.0000300782,0.00008774531,0.0001015352,0.0001772686,0.00005085026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000072034,"about_ca_system_score_gemma":0.00006519754,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1279521,"about_ca_topic_score_gemma":0.9781637,"domain_scores_codex":[0.9986587,0.0000402764,0.0002217829,0.0005174191,0.0001771037,0.0003847612],"domain_scores_gemma":[0.9994484,0.0001591944,0.0001456051,0.00007275031,0.00008599155,0.00008810656],"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":[0.0001534571,0.00001412473,0.0002978164,0.00009766559,0.00002886047,0.00001322804,0.00001065764,0.00000840146,0.00003012128,6.311064e-7,0.9964718,0.002873252],"study_design_scores_gemma":[0.0005699141,0.000163983,0.02363939,0.00199299,0.00002894129,0.00001248088,0.00003875145,0.0003661979,0.0000489845,0.00008302583,0.9724539,0.00060142],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.006664171,0.001390353,4.117214e-7,0.0001920776,0.0001097994,0.0004098082,0.9911855,0.0000219458,0.00002589726],"genre_scores_gemma":[0.01817933,0.00003866018,0.000002829865,0.0001723484,0.0001506331,0.00007822226,0.9808252,0.000002797705,0.0005499741],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8502116,"threshold_uncertainty_score":0.9994655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03331009849277809,"score_gpt":0.2351848173411827,"score_spread":0.2018747188484046,"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."}}