{"id":"W2158871915","doi":"10.1890/07-1526.1","title":"AN INCIDENCE-BASED RICHNESS ESTIMATOR FOR QUADRATS SAMPLED WITHOUT REPLACEMENT","year":2008,"lang":"en","type":"article","venue":"Ecology","topic":"Census and Population Estimation","field":"Mathematics","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Council","keywords":"Quadrat; Species richness; Estimator; Statistics; Mathematics; Sampling (signal processing); Poisson distribution; Negative binomial distribution; Poisson sampling; Variance (accounting); Sampling design; Ecology; Econometrics; Biology; Computer science; Importance sampling; Slice sampling; Population; Filter (signal processing); Demography; Transect","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":[0.000324658,0.0001109901,0.0002240316,0.00007252504,0.0002474539,0.000008693019,0.0000969869,0.00009973362,0.0002852968],"category_scores_gemma":[0.0005865144,0.0001053618,0.00004286168,0.0000779237,0.00004456607,0.00008782239,0.00001085228,0.00005307933,0.00002526078],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008234147,"about_ca_system_score_gemma":0.0001179534,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002181619,"about_ca_topic_score_gemma":0.000280958,"domain_scores_codex":[0.9990894,0.00007180702,0.0003133579,0.0002128973,0.0001084645,0.000204071],"domain_scores_gemma":[0.9988592,0.0004678248,0.000182827,0.0002891733,0.0001321367,0.00006890051],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004670239,0.0006513151,0.9247971,0.00016519,0.00003432878,0.00001049771,0.0008415619,0.002283468,0.0005147872,0.05768889,0.01178992,0.0007558988],"study_design_scores_gemma":[0.003771006,0.001146317,0.5088713,0.00002693761,0.00008294289,0.00006916779,0.00005680092,0.4092076,0.001296912,0.07098576,0.003996379,0.0004888753],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8429688,0.000004076297,0.1556037,0.0003545198,0.0002460852,0.0005618675,0.00001261679,0.000110946,0.0001374065],"genre_scores_gemma":[0.8373021,5.503666e-7,0.1620315,0.000196812,0.00007491607,0.0001552517,0.00007680031,0.0000179186,0.0001442211],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4159258,"threshold_uncertainty_score":0.4296529,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08667446144113708,"score_gpt":0.374878874080984,"score_spread":0.2882044126398469,"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."}}