{"id":"W6960745857","doi":"10.1371/journal.pone.0034025.t005","title":"Regression results for mean annual fatalities by tower height, when unadjusted, corrected for sampling only, corrected for search efficiency and scavenging only, and corrected for both sampling and search efficiency/scavenging, with estimated annual fatalities after back transformation, adjustment for bias, and application to all towers in the United States and Canada.","year":2015,"lang":"en","type":"dataset","venue":"Figshare","topic":"Wheat and Barley Genetics and Pathology","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sampling (signal processing); Scavenging; Regression analysis; Tower; Regression","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001662775,0.001665519,0.001182427,0.002998986,0.000564325,0.001350689,0.002631831,0.001040867,0.04202053],"category_scores_gemma":[0.01180585,0.0005812786,0.001874647,0.004753099,0.0002937834,0.001187157,0.001488494,0.00165148,0.02590547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002330477,"about_ca_system_score_gemma":0.003422592,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2799951,"about_ca_topic_score_gemma":0.4045722,"domain_scores_codex":[0.9987813,0.0001766613,0.0001516356,0.0003887437,0.0003394319,0.0001621642],"domain_scores_gemma":[0.993799,0.001338543,0.001017653,0.0006605421,0.002917345,0.0002669153],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00006258668,0.00001376379,0.00759961,0.0005324814,0.0001822887,0.00001516523,0.00002049382,0.0007368984,0.00005027068,0.0005085845,0.9877532,0.002524585],"study_design_scores_gemma":[0.0005094648,0.00003305873,0.08946689,0.0009432981,0.0004831337,0.0001029452,0.000315885,0.002038747,0.0004593077,0.001386783,0.9041761,0.00008442189],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004049264,0.0001100114,0.0001598097,0.00008766463,0.00003589281,0.00001291828,0.9982007,0.0001441524,0.000843923],"genre_scores_gemma":[0.002920928,0.0001003814,0.0007059636,0.0001032714,0.00002037895,0.0001316038,0.9919429,0.0001226424,0.003951984],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7200049,"threshold_uncertainty_score":0.5567306,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05631401915604827,"score_gpt":0.2845791116152503,"score_spread":0.2282650924592021,"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."}}