{"id":"W2102667639","doi":"10.1007/s10750-011-0846-6","title":"Species–area relationships arise from interaction of habitat heterogeneity and species pool","year":2011,"lang":"en","type":"article","venue":"Hydrobiologia","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor; McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Habitat; Species richness; Spatial heterogeneity; Ecology; Microcosm; Biodiversity; Spatial ecology; Invertebrate; Interspecific competition; Scale (ratio); Species diversity; Biology; Geography","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":[0.0001337673,0.00008670933,0.0001261521,0.00002305488,0.0001321965,0.000004023563,0.00007892949,0.00008252215,0.0007880478],"category_scores_gemma":[0.0001002777,0.00007253225,0.00003174943,0.00005981292,0.0003838665,0.0001208921,0.0001340836,0.0001215385,0.0001332326],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004004693,"about_ca_system_score_gemma":0.000001972584,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001235181,"about_ca_topic_score_gemma":0.004109237,"domain_scores_codex":[0.9994092,0.00008009248,0.0001742414,0.0001924995,0.00003803021,0.0001059114],"domain_scores_gemma":[0.9995769,0.0001572602,0.0001089305,0.0001225663,0.000007637769,0.0000267235],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001969566,0.00004114108,0.9899051,0.000001588001,0.00002187233,0.000001069943,0.0006211148,0.00008682658,0.008776871,0.0002556124,0.0002278338,0.00004129403],"study_design_scores_gemma":[0.0001103647,0.000059061,0.9932137,0.000004628853,0.00001525756,0.000002213659,0.0002762669,0.0006091621,0.003668859,0.001821178,0.0001407804,0.00007848467],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9828227,0.00004367229,0.0004666789,0.00004033074,0.0001347737,0.0000865839,0.00002343436,0.00002217668,0.01635963],"genre_scores_gemma":[0.9982791,0.00005552018,0.00126412,0.0000377079,0.000008940709,0.000007050976,0.00002291333,0.000003443571,0.0003212066],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01603842,"threshold_uncertainty_score":0.862857,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05819655489177005,"score_gpt":0.2303391244953079,"score_spread":0.1721425696035379,"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."}}