{"id":"W2112837855","doi":"10.1111/j.1600-0706.2011.19679.x","title":"A framework for estimating niche metrics using the resemblance between qualitative resources","year":2011,"lang":"en","type":"article","venue":"Oikos","topic":"Plant and animal studies","field":"Agricultural and Biological Sciences","cited_by":93,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Niche; Toolbox; Resource (disambiguation); Ecological niche; Niche differentiation; Ecology; Bootstrapping (finance); Environmental niche modelling; Set (abstract data type); Resource distribution; Niche segregation; Computer science; Habitat; Biology; Econometrics; Mathematics; Resource allocation","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":[0.0005166468,0.00008037104,0.0001345241,0.000006035911,0.0004487921,0.0000326597,0.0002084898,0.00005138101,0.00002040066],"category_scores_gemma":[0.0007536542,0.00002319922,0.00005858408,0.0002837554,0.00005857909,0.00003527845,0.00006058809,0.00009198153,0.000005363747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007639476,"about_ca_system_score_gemma":0.000001444616,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002085262,"about_ca_topic_score_gemma":0.0001199145,"domain_scores_codex":[0.9993319,0.00008633701,0.0001256891,0.0001443546,0.0001161297,0.000195623],"domain_scores_gemma":[0.9976084,0.002203961,0.0000950903,0.00001968776,0.00004414063,0.00002868621],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005159879,0.0002619378,0.4010006,0.0001712557,0.0005755314,0.00000982851,0.1422375,0.00002159135,0.07458559,0.04629733,0.007858854,0.326464],"study_design_scores_gemma":[0.0004623884,0.001886049,0.6097932,0.0005616198,0.0002791426,0.000007771873,0.07034235,0.007880851,0.01027089,0.24162,0.05543947,0.001456319],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99478,0.0002192733,0.003474044,0.0004128553,0.00003605029,0.0001385105,0.00004795709,0.00003378139,0.0008575291],"genre_scores_gemma":[0.9535946,0.000005601423,0.04568989,0.0001160333,0.0005144681,0.00001398589,0.000003023082,7.12714e-7,0.00006170708],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3250077,"threshold_uncertainty_score":0.3451791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3883642458858651,"score_gpt":0.3689637576860533,"score_spread":0.01940048819981177,"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."}}