{"id":"W6892128786","doi":"10.5063/aa/bowdish.819.1","title":"Activity trap data MERP cells 1985-1989","year":2007,"lang":"en","type":"dataset","venue":"UC Santa Barbara","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ducks Unlimited Canada","funders":"","keywords":"Marsh; Invertebrate; Wetland; Functional ecology; State (computer science)","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":[],"consensus_categories":[],"category_scores_codex":[0.0008392487,0.001626438,0.001315018,0.004205863,0.0006235903,0.001433321,0.002186683,0.0008755612,0.03526518],"category_scores_gemma":[0.00359665,0.000736763,0.0006768804,0.008443794,0.0002057451,0.0007640651,0.001128617,0.00110127,0.04982097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001450996,"about_ca_system_score_gemma":0.001725481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0540168,"about_ca_topic_score_gemma":0.06929887,"domain_scores_codex":[0.9987661,0.0001224339,0.0001816399,0.0003425564,0.0004289324,0.0001583005],"domain_scores_gemma":[0.9972686,0.0002825169,0.0006649749,0.0004235178,0.001191285,0.0001692063],"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":[0.0001024264,0.00004161306,0.008718031,0.0003755191,0.00004763714,0.00004012183,0.00003461338,0.0003968049,0.0001069497,0.0003649007,0.9844765,0.005294972],"study_design_scores_gemma":[0.0002033554,0.00003804779,0.06039139,0.0003046932,0.00005370595,0.0001090858,0.0001711933,0.0007783627,0.0006225429,0.0005118701,0.9367808,0.00003490399],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004939529,0.0000346225,0.00004335902,0.00001833809,0.000006252585,0.00001013021,0.9987704,0.00006152353,0.0005613049],"genre_scores_gemma":[0.001166005,0.00004208947,0.0001948125,0.00001728591,0.000004968733,0.00009532291,0.997445,0.00002461216,0.001009937],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0540168,"threshold_uncertainty_score":0.1179737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06901451934197668,"score_gpt":0.3420312238823333,"score_spread":0.2730167045403566,"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."}}