{"id":"W2021341266","doi":"10.1007/s10144-009-0175-z","title":"Quantitative descriptions of resource choice in ecological models","year":2009,"lang":"en","type":"article","venue":"Population Ecology","topic":"Plant and animal studies","field":"Agricultural and Biological Sciences","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Resource (disambiguation); Ecology; Population; Biology; Variety (cybernetics); Stability (learning theory); Microeconomics; Economics; Computer science","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":[0.0001048444,0.00005487695,0.0001448546,0.00001584199,0.00007170344,0.000004229777,0.00006842497,0.00006702799,0.00007244833],"category_scores_gemma":[0.00009406001,0.00002296999,0.00003144065,0.0001698154,0.00002313027,0.00007181766,0.00001595503,0.00005460052,0.00000584224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001895429,"about_ca_system_score_gemma":0.000001274791,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002562819,"about_ca_topic_score_gemma":0.03015365,"domain_scores_codex":[0.9994463,0.00006662864,0.0001806425,0.0001207603,0.00004976273,0.0001359073],"domain_scores_gemma":[0.9996424,0.0002396826,0.00006676425,0.000009279209,0.0000215683,0.00002027478],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004652622,0.0002132481,0.9587314,0.000001198819,0.000003890434,0.000001991916,0.00007242495,0.0007700429,0.01300457,0.02333657,0.0002387756,0.003579416],"study_design_scores_gemma":[0.00007014676,0.0003883222,0.9832176,0.00000303331,0.000002596799,7.363155e-7,0.0001127753,0.001391541,0.00001705093,0.01454465,0.000200118,0.000051409],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958916,0.00004852429,0.000003122942,0.001343403,0.00001541647,0.00008520772,0.00001209406,0.00001950686,0.002581076],"genre_scores_gemma":[0.9995267,0.00001193989,0.0001398918,0.0002092555,0.00002590305,0.000004471493,0.00003150824,1.638513e-7,0.00005011172],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02989737,"threshold_uncertainty_score":0.9875435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1284415004463457,"score_gpt":0.2753505756651548,"score_spread":0.1469090752188091,"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."}}