{"id":"W2771754487","doi":"10.1038/s41467-017-02157-0","title":"A mechanistic theory for aquatic food chain length","year":2017,"lang":"en","type":"article","venue":"Nature Communications","topic":"Isotope Analysis in Ecology","field":"Environmental Science","cited_by":94,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Productivity; Ecosystem; Food chain; Context (archaeology); Biomass (ecology); Environmental science; Aquatic ecosystem; Flux (metallurgy); Marine ecosystem; Ecology; Natural resource economics; Biology; Economics; Chemistry","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":[0.001737081,0.0008213624,0.0004814891,0.001505056,0.001028969,0.002043242,0.001955984,0.001781327,0.008140286],"category_scores_gemma":[0.004072425,0.0004000319,0.001048012,0.0009694697,0.003700512,0.005394278,0.002040959,0.001316536,0.001191124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001372162,"about_ca_system_score_gemma":0.0007960124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009880507,"about_ca_topic_score_gemma":0.0006360144,"domain_scores_codex":[0.9995195,0.0001098132,0.00002144034,0.0001842612,0.0001145348,0.0000504657],"domain_scores_gemma":[0.9987035,0.0005632434,0.0003059342,0.0001651739,0.0001484392,0.0001136197],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004675587,0.00006632015,0.008587981,0.0003260674,0.0001207142,0.0001723245,0.0003100619,0.02600433,0.002658311,0.9300166,0.00265344,0.02903702],"study_design_scores_gemma":[0.00001707897,0.0000726248,0.004493173,0.00005967917,0.00002831325,0.0002786891,0.0001020218,0.02409562,0.0003574718,0.9636118,0.00684524,0.00003832829],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1222194,0.006854175,0.773777,0.01758394,0.000814507,0.0001600817,0.00115513,0.0005729118,0.07686282],"genre_scores_gemma":[0.9341396,0.003781957,0.04790036,0.002600997,0.0007799748,0.0005786882,0.0004033774,0.0001131381,0.009701909],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008140286,"threshold_uncertainty_score":0.02723199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02274025983489874,"score_gpt":0.3043097048102311,"score_spread":0.2815694449753324,"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."}}