{"id":"W6960888473","doi":"10.1371/journal.pone.0208911.t003","title":"Model selection results using BIC forward-backward search for each mosquito species of the Greater Golden Horseshoe region, Ontario, Canada.","year":2018,"lang":"en","type":"dataset","venue":"Figshare","topic":"Genetic and Environmental Crop Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Selection (genetic algorithm); Horseshoe (symbol); Horseshoe crab; Key (lock); Model selection","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":[0.002506152,0.003524761,0.001856407,0.00244524,0.002207497,0.002369267,0.004985561,0.002468974,0.05428909],"category_scores_gemma":[0.01256591,0.000845051,0.002825617,0.003502589,0.0009001276,0.0009754992,0.001271359,0.002417233,0.03232438],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01183152,"about_ca_system_score_gemma":0.02500719,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8838019,"about_ca_topic_score_gemma":0.9615989,"domain_scores_codex":[0.9988984,0.0001948459,0.00007941068,0.0003683242,0.0002736862,0.0001853653],"domain_scores_gemma":[0.9954086,0.001365117,0.0001677358,0.0005522286,0.002160702,0.000345507],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007424097,0.00001962728,0.002747922,0.0003888181,0.0001193036,0.00002919791,0.00002816932,0.00203208,0.00006111748,0.0003117092,0.9912633,0.00292461],"study_design_scores_gemma":[0.001957356,0.00004379397,0.03347594,0.001334936,0.0006829597,0.0001281489,0.0004635094,0.01605121,0.0006746329,0.004320974,0.9407007,0.0001658564],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0009810738,0.0003473962,0.0004573298,0.000291144,0.00007804511,0.00003204618,0.9952893,0.00088067,0.001642932],"genre_scores_gemma":[0.003471174,0.0001150502,0.00160297,0.00009641046,0.00001419221,0.0001247004,0.9917024,0.0003303546,0.002542855],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1161981,"threshold_uncertainty_score":0.2337647,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1111332297633837,"score_gpt":0.2354546229740498,"score_spread":0.1243213932106661,"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."}}