{"id":"W4404579798","doi":"10.1002/ecy.4467","title":"Publication‐driven consistency in food web structures: Implications for comparative ecology","year":2024,"lang":"en","type":"article","venue":"Ecology","topic":"Plant and animal studies","field":"Agricultural and Biological Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland; Université de Montréal; Université de Sherbrooke; St. Michael's Hospital; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Food web; Ecology; Consistency (knowledge bases); Community structure; Similarity (geometry); Ecological network; Inference; Computer science; Data science; Geography; Ecosystem; Biology; Artificial intelligence","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0680446,0.0007235321,0.001169552,0.009532916,0.00185604,0.005320993,0.002934882,0.00149382,0.008825004],"category_scores_gemma":[0.2248481,0.0006066464,0.002764258,0.01378512,0.005138807,0.009867395,0.004429574,0.001456149,0.0007299699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001466604,"about_ca_system_score_gemma":0.002075567,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003400818,"about_ca_topic_score_gemma":0.004164122,"domain_scores_codex":[0.9605851,0.02114527,0.003386091,0.008713502,0.004755728,0.001414267],"domain_scores_gemma":[0.6902106,0.1959374,0.04341632,0.05442325,0.01258236,0.003430084],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003600769,0.0001377411,0.8748306,0.001228516,0.005424812,0.0004267466,0.006920722,0.002163949,0.002124508,0.03650873,0.00324083,0.06663271],"study_design_scores_gemma":[0.00005090012,0.0002097138,0.9031582,0.000451914,0.001024145,0.0004858742,0.003487601,0.005982319,0.001501053,0.07487337,0.008651717,0.0001230916],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8388149,0.01008557,0.1074172,0.008526818,0.0008933451,0.0005294752,0.005650809,0.000725361,0.02735652],"genre_scores_gemma":[0.9778766,0.0006442202,0.01797098,0.0006220905,0.0001872897,0.0002136066,0.001595576,0.0001503427,0.0007391524],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9319554,"threshold_uncertainty_score":0.3598585,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09569216400210291,"score_gpt":0.2866423301906725,"score_spread":0.1909501661885696,"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."}}