{"id":"W1818586158","doi":"10.1111/oik.02838","title":"A new cost‐effective approach to survey ecological communities","year":2015,"lang":"en","type":"article","venue":"Oikos","topic":"Forest Ecology and Biodiversity Studies","field":"Agricultural and Biological Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Université de Montréal; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Quadrat; Sampling (signal processing); Transect; Ecology; Abundance (ecology); Statistics; Global biodiversity; Relative species abundance; Unit (ring theory); Environmental science; Mathematics; Biology; Computer science; Biodiversity","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003084715,0.000949888,0.00120721,0.005719683,0.0005731679,0.001976934,0.002567766,0.0009415344,0.008216382],"category_scores_gemma":[0.00671201,0.00070314,0.000800978,0.005090882,0.0008348456,0.002678762,0.002030832,0.001053,0.002280032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001571676,"about_ca_system_score_gemma":0.001117094,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009271197,"about_ca_topic_score_gemma":0.02255965,"domain_scores_codex":[0.9958691,0.001070199,0.0001527416,0.000623845,0.002164186,0.0001197965],"domain_scores_gemma":[0.9955772,0.001376574,0.0004362887,0.001323781,0.001062238,0.0002240018],"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":[0.0002867539,0.0003198836,0.016302,0.000851227,0.0004321537,0.0001748413,0.0004778021,0.009718134,0.03791569,0.02543029,0.0104713,0.8976199],"study_design_scores_gemma":[0.0005867202,0.00238754,0.1300692,0.0006978081,0.001372858,0.004735915,0.002300919,0.3484135,0.04967044,0.1829725,0.2760547,0.0007379497],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01834202,0.0009687029,0.9673405,0.001002302,0.0002025553,0.0005302479,0.001953897,0.001012656,0.008647107],"genre_scores_gemma":[0.09381615,0.0007178941,0.8966343,0.0003522668,0.000111063,0.001028494,0.001025721,0.0001258459,0.006188283],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009271197,"threshold_uncertainty_score":0.02748656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09520159066925182,"score_gpt":0.2435888456751447,"score_spread":0.1483872550058928,"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."}}