{"id":"W2017290159","doi":"10.1371/journal.pone.0056171","title":"Separating the Effects of Environment and Space on Tree Species Distribution: From Population to Community","year":2013,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China","keywords":"Understory; Edaphic; Biological dispersal; Ecology; Species distribution; Spatial ecology; Spatial variability; Spatial distribution; Population; Biology; Habitat; Geography; Statistics; Canopy; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.001059556,0.0002932725,0.0003372229,0.001051185,0.0002468386,0.0004970458,0.0002736249,0.000162077,0.0006270643],"category_scores_gemma":[0.002562785,0.0001916439,0.0004464426,0.0007267399,0.0004314462,0.0007194771,0.0006412312,0.000227485,0.00009399815],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003129155,"about_ca_system_score_gemma":0.0003745294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008284183,"about_ca_topic_score_gemma":0.01606523,"domain_scores_codex":[0.9994208,0.0001775757,0.00003461998,0.0002186093,0.00008012394,0.00006819695],"domain_scores_gemma":[0.9983162,0.0008114614,0.0002739844,0.00018615,0.0002274018,0.0001848582],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004350329,0.00002536005,0.9777876,0.00002996417,0.0001621364,0.00006663087,0.0003371586,0.0009777137,0.005360425,0.0001521725,0.00006544002,0.01499198],"study_design_scores_gemma":[0.00000242801,0.00002370052,0.9929427,0.000003274456,0.00002621251,0.00004371308,0.0001314905,0.006395585,0.0002040069,0.0001476909,0.00007296566,0.000006398236],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984573,0.00008328804,0.001173191,0.00001267951,0.000002082798,0.000004543369,0.0000696428,0.000008511606,0.0001887375],"genre_scores_gemma":[0.9993548,0.00002615741,0.0004540212,0.000005337507,0.000002557052,0.000004452617,0.00009976919,0.000002477853,0.00005038036],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008284183,"threshold_uncertainty_score":0.01647192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0177461440066265,"score_gpt":0.2003539988784455,"score_spread":0.182607854871819,"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."}}