{"id":"W2063630081","doi":"10.1007/s10531-015-0873-0","title":"Influence of traffic mortality on forest bird abundance","year":2015,"lang":"en","type":"article","venue":"Biodiversity and Conservation","topic":"Wildlife-Road Interactions and Conservation","field":"Environmental Science","cited_by":33,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada; Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Abundance (ecology); Geography; Ecology; Relative species abundance; Biodiversity; Environmental science; Collision; Traffic volume; Physical geography; Biology; Transport engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000139632,0.00006361528,0.00007093026,0.00002519707,0.00009310518,0.00001407704,0.00007479319,0.00004174912,0.00003635238],"category_scores_gemma":[0.00004897153,0.00006366942,0.00001929411,0.0001439077,0.0001499469,0.0003616464,0.00004414192,0.00004716741,0.0001747759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005149647,"about_ca_system_score_gemma":0.0000144903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003276662,"about_ca_topic_score_gemma":0.001164321,"domain_scores_codex":[0.9994701,0.00002792137,0.000112138,0.0001461267,0.0001696493,0.00007407447],"domain_scores_gemma":[0.9996766,0.00002691759,0.00009095748,0.0001164885,0.00003217514,0.00005682788],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004765484,0.0000482102,0.986028,0.000004333955,0.000005467436,8.172514e-7,0.0002140974,0.008293347,0.0002260782,0.0001075977,0.004475277,0.0005491066],"study_design_scores_gemma":[0.0002471696,0.0000873328,0.9918483,0.00001002522,0.0000115275,0.000001252582,0.0001205548,0.002221746,0.0001496289,0.00009063214,0.005139398,0.00007245481],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983083,0.000005667193,0.00002211615,0.001124019,0.00003982375,0.00009073085,0.00001146088,0.00003284669,0.0003650051],"genre_scores_gemma":[0.9989046,0.00001058647,0.00008409,0.0009287603,0.000005958482,0.000002126901,0.000007110152,0.000001604668,0.00005519571],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006071601,"threshold_uncertainty_score":0.4953355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0348309250656855,"score_gpt":0.2290157376703288,"score_spread":0.1941848126046433,"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."}}