{"id":"W6907534214","doi":"10.2192/1537-6176(2004)015&lt;0123:gbrpit&gt;2.0.co;2","title":"Grizzly bear recovery planning in the British Columbia portion of the North Cascades: Lessons learned and re-learned","year":2004,"lang":"en","type":"article","venue":"BioOne Complete (BioOne)","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Grizzly Bears; Population; Strengths and weaknesses; Plan (archaeology); Ecosystem","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":[0.002813834,0.0003612211,0.0002728267,0.000994612,0.004145308,0.002302168,0.002481974,0.001113348,0.004323081],"category_scores_gemma":[0.004350442,0.0002425016,0.0002101749,0.0008942492,0.001287892,0.001629482,0.002002314,0.00183614,0.0002862907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008304438,"about_ca_system_score_gemma":0.04245814,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7935586,"about_ca_topic_score_gemma":0.9250198,"domain_scores_codex":[0.9987366,0.0002749973,0.00004205689,0.00009368419,0.0003767136,0.0004760217],"domain_scores_gemma":[0.9972433,0.0004697303,0.000148499,0.0001702676,0.0009119126,0.001056265],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002887367,0.0008902096,0.1022509,0.001122181,0.00009955846,0.003641487,0.01200974,0.02362613,0.002501247,0.01014453,0.07993106,0.7634943],"study_design_scores_gemma":[0.0001747122,0.0008960154,0.4408994,0.004066146,0.0002116551,0.001152866,0.1598081,0.01988833,0.004195483,0.01352143,0.3549042,0.0002817294],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7191501,0.01014979,0.008761971,0.1481561,0.0003699169,0.001310102,0.0009355947,0.0003273301,0.1108391],"genre_scores_gemma":[0.9498762,0.01068787,0.01622977,0.003801128,0.00009878966,0.0003487216,0.0006286296,0.00005080341,0.01827817],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2064414,"threshold_uncertainty_score":0.4153143,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2081916888008786,"score_gpt":0.2494826403660363,"score_spread":0.04129095156515764,"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."}}