{"id":"W2185060673","doi":"10.1007/s10980-015-0298-x","title":"Grain-dependent functional responses in habitat selection","year":2015,"lang":"en","type":"article","venue":"Landscape Ecology","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":41,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta; University of Saskatchewan","funders":"","keywords":"Habitat; Odocoileus; Ecology; Functional response; Home range; Landscape ecology; Selection (genetic algorithm); Range (aeronautics); Spatial ecology; Biology; Predation; Machine learning; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004908693,0.00007308236,0.00009646088,0.0000629299,0.00006203121,0.000006790277,0.00007314597,0.0001279118,0.002429727],"category_scores_gemma":[0.0002041815,0.00007056801,0.00001865908,0.0001796395,0.00005833768,0.0001294324,0.00005921117,0.0001285106,0.001470707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001578126,"about_ca_system_score_gemma":0.00004469572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006370425,"about_ca_topic_score_gemma":0.01509283,"domain_scores_codex":[0.9991555,0.0001717934,0.0001494695,0.0002108191,0.0001063267,0.0002061564],"domain_scores_gemma":[0.9996838,0.0001233616,0.00004514192,0.00007600014,0.00001004733,0.00006162959],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001845964,0.00006497601,0.9628702,5.695076e-7,0.000003641158,0.000009859905,0.00009318084,0.001028753,0.00008666348,0.0001560906,0.03533787,0.0001635653],"study_design_scores_gemma":[0.0007336381,0.0001598433,0.9920643,6.953096e-7,0.000003949434,0.00004127591,0.00007633792,0.0009707992,0.00002905318,0.002135754,0.003704814,0.00007952208],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9881626,0.000008803752,0.0000877072,0.001913917,0.0005868141,0.0001027588,0.000001097338,0.0000360204,0.009100216],"genre_scores_gemma":[0.9948006,0.000002222399,0.0001659733,0.001190471,0.00006581499,0.00004853618,0.00001165764,0.000005555586,0.003709136],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03163306,"threshold_uncertainty_score":0.9993067,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01788573878379558,"score_gpt":0.2258115754533728,"score_spread":0.2079258366695772,"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."}}