{"id":"W2893485273","doi":"10.3390/d10040104","title":"Seasonal Use of Railways by Wildlife","year":2018,"lang":"en","type":"article","venue":"Diversity","topic":"Wildlife-Road Interactions and Conservation","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Laurentian University; Mount Allison University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Wildlife; Ecology; Baseline (sea); Wildlife conservation; Geography; Wildlife management; Fauna; Nocturnal; Diel vertical migration; Wildlife corridor; Environmental resource management; Fishery; Biology; Environmental science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00004631722,0.00004039383,0.00004446739,0.00000881352,0.0001847546,0.000009099263,0.00009610039,0.00002331298,0.004034797],"category_scores_gemma":[0.00002335893,0.00004038377,0.00002790513,0.00008581167,0.0001541223,0.0003528556,0.0002918432,0.00003259693,0.0005143248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000439549,"about_ca_system_score_gemma":0.00000315163,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001957885,"about_ca_topic_score_gemma":0.0000733555,"domain_scores_codex":[0.9996006,0.00001588188,0.00005319265,0.0001054309,0.0001483684,0.00007649535],"domain_scores_gemma":[0.9997856,0.00001995835,0.00004071627,0.0001009593,0.00001362041,0.00003911792],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001364182,0.00003239731,0.6688876,4.670402e-7,0.000004361933,2.606285e-7,0.0001197686,0.000003890706,0.001100924,0.00002573847,0.3287607,0.001050237],"study_design_scores_gemma":[0.0001264655,0.00004916358,0.7645622,0.000003270372,0.000009033852,7.977519e-7,0.0000444586,0.000741902,0.00110925,0.00003885563,0.2332486,0.00006600995],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950913,0.000001184855,0.0004008755,0.0003116624,0.00008834611,0.00003529083,0.00003098467,0.00001329832,0.004027048],"genre_scores_gemma":[0.9970097,0.000002514418,0.0003694849,0.001015025,0.00002005692,3.74334e-7,0.000008008133,0.000001720826,0.00157313],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09567459,"threshold_uncertainty_score":0.9968756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0245773306944373,"score_gpt":0.2133779791978314,"score_spread":0.1888006485033941,"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."}}