{"id":"W2155952072","doi":"10.1007/978-1-4020-6850-8_11","title":"Comments On “Predictive Modelling Of Patch Use By Terrestrial Herbivores”","year":2007,"lang":"en","type":"book-chapter","venue":"","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ontario Forest Research Institute","funders":"","keywords":"Herbivore; Forage; Food intake; Resource use; Resource (disambiguation); Ecology; Selection (genetic algorithm); Livestock; Geography; Environmental science; Computer science; Environmental resource management; Biology; Machine learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004013874,0.001038686,0.000919282,0.0007571858,0.002240918,0.00227862,0.003412199,0.01102089,0.03040363],"category_scores_gemma":[0.02271701,0.0006645673,0.001373533,0.001558711,0.002074616,0.004447222,0.001556645,0.01062611,0.01671858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00225592,"about_ca_system_score_gemma":0.001984832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03696683,"about_ca_topic_score_gemma":0.04591645,"domain_scores_codex":[0.9979145,0.0006127511,0.000165438,0.00028386,0.0008603958,0.0001630304],"domain_scores_gemma":[0.9875622,0.006705876,0.0004301181,0.0005077252,0.004369085,0.0004250156],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001044421,0.00000495139,0.00006797629,0.00003485195,0.000004174995,0.00003890345,0.00007312284,0.0004116211,0.00007572592,0.004179166,0.9913279,0.00377117],"study_design_scores_gemma":[0.000009063878,0.00001264519,0.0007090099,0.0001758265,0.00001278592,0.0001016524,0.0001868544,0.001609225,0.0003208709,0.01249955,0.9843193,0.00004336283],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.001053739,0.00513288,0.01098325,0.7954769,0.1428577,0.00005407156,0.001169288,0.0004480858,0.04282418],"genre_scores_gemma":[0.01198811,0.00499184,0.008368629,0.6957743,0.06610352,0.0001706975,0.000797326,0.0009872074,0.2108185],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.03696683,"threshold_uncertainty_score":0.1017102,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0616402168363293,"score_gpt":0.2353807556668082,"score_spread":0.1737405388304789,"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."}}