{"id":"W3026847252","doi":"10.1111/ele.13525","title":"Co‐occurrence is not evidence of ecological interactions","year":2020,"lang":"en","type":"article","venue":"Ecology Letters","topic":"Plant and animal studies","field":"Agricultural and Biological Sciences","cited_by":820,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Ecology; Proxy (statistics); Null model; Community; Co-occurrence; Ecological systems theory; Spatial analysis; Geography; Biology; Computer science; Habitat; Machine learning; Artificial intelligence; Remote sensing","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004766822,0.0002482715,0.001040691,0.001952896,0.001132122,0.00178253,0.001195294,0.001434688,0.003682436],"category_scores_gemma":[0.03737278,0.0003395657,0.0003312208,0.00269332,0.00332399,0.003222063,0.002218348,0.001385987,0.0005891296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003966111,"about_ca_system_score_gemma":0.0003448372,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001138448,"about_ca_topic_score_gemma":0.001965699,"domain_scores_codex":[0.9928851,0.002041458,0.0007025795,0.002596535,0.001295713,0.0004786319],"domain_scores_gemma":[0.9127299,0.05331055,0.01823872,0.009392785,0.003264886,0.003063148],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006038652,0.0001445246,0.9436489,0.0004610511,0.0006301502,0.0009060561,0.001494586,0.0006414761,0.005691318,0.00844255,0.001229719,0.03610586],"study_design_scores_gemma":[0.00002620303,0.0002632796,0.9498871,0.0001104534,0.0002692507,0.005402971,0.002608804,0.005224625,0.001513578,0.03066091,0.003964895,0.00006781612],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9787482,0.0007990659,0.007056276,0.001444682,0.00007038519,0.00002070329,0.000389549,0.00003787304,0.01143332],"genre_scores_gemma":[0.9987011,0.00008739823,0.0007205447,0.0001119585,0.00004243698,0.00001022349,0.0001420201,0.000005212715,0.0001792213],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004766822,"threshold_uncertainty_score":0.02520967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1348709647601323,"score_gpt":0.2770431480248636,"score_spread":0.1421721832647312,"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."}}