{"id":"W6923943088","doi":"10.14288/1.0089522","title":"A comparison of trapping methodologies and grid size for small mammal research","year":2009,"lang":"en","type":"article","venue":"cIRcle (University of British Columbia)","topic":"Healthcare innovation and challenges","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Trapping; Replicate; Population; Mammal; Grid cell; Grid; Field (mathematics)","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":[0.01760745,0.0005237158,0.000742723,0.001525362,0.000517181,0.000922098,0.001259946,0.0005047912,0.001705066],"category_scores_gemma":[0.04941449,0.0005704578,0.000349608,0.001224642,0.0004440364,0.001345737,0.0009432988,0.0003822584,0.0003244816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000908333,"about_ca_system_score_gemma":0.001029024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007593915,"about_ca_topic_score_gemma":0.02383805,"domain_scores_codex":[0.9785513,0.01542743,0.001107103,0.001392941,0.003207203,0.0003139173],"domain_scores_gemma":[0.9543818,0.03091958,0.003452247,0.004506905,0.006086753,0.0006527689],"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":[0.004771065,0.001016095,0.2132342,0.002465253,0.0005923171,0.0001527063,0.00224443,0.0058082,0.02598331,0.002650093,0.003284864,0.7377974],"study_design_scores_gemma":[0.0017846,0.01335277,0.8603417,0.001832554,0.001011927,0.002055999,0.003136427,0.04732198,0.02472202,0.004254603,0.03976746,0.0004178701],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7005559,0.01634059,0.2570057,0.001506136,0.0009222329,0.004738559,0.001947988,0.001110084,0.01587268],"genre_scores_gemma":[0.5315457,0.008479639,0.4490398,0.0006596233,0.0002429279,0.004897073,0.001088624,0.000352583,0.003693987],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01760745,"threshold_uncertainty_score":0.09311819,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2816465887929401,"score_gpt":0.4183571140514118,"score_spread":0.1367105252584717,"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."}}