{"id":"W4378085109","doi":"10.3390/agronomy13051432","title":"Quantifying and Disentangling the Competition Effect of a Weed Community in a Long-Term Biennial Cereal-Legume Rotation","year":2023,"lang":"en","type":"article","venue":"Agronomy","topic":"Weed Control and Herbicide Applications","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Ministerio de Ciencia e Innovación; University of Guelph","keywords":"Interspecific competition; Weed; Biology; Competition (biology); Intraspecific competition; Agronomy; Population; Ecology","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":[0.0003448516,0.00005679144,0.000100944,0.00001334907,0.0002064609,0.00002643123,0.00009722898,0.00002676939,0.00001918315],"category_scores_gemma":[0.00001457888,0.00002036422,0.00003166449,0.0002640671,0.00005001024,0.00006267695,0.00004500444,0.00009300239,0.000009545081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009735155,"about_ca_system_score_gemma":0.000001935223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004860666,"about_ca_topic_score_gemma":0.007823948,"domain_scores_codex":[0.9994765,0.000165814,0.0001233637,0.00007957021,0.00005275182,0.0001020131],"domain_scores_gemma":[0.9992708,0.0005989085,0.00005355663,0.00004343666,0.00001291005,0.00002040652],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005740936,0.00004355888,0.6718627,0.00003424348,0.00001325313,0.000001000558,0.0006269489,0.0000253701,0.25849,0.001645111,0.00001550023,0.06718491],"study_design_scores_gemma":[0.0002136003,0.00007352992,0.9981532,0.0000305359,0.000009669811,7.146372e-7,0.0003305329,0.0004101624,0.0004641174,0.0002317054,0.00003841898,0.00004387215],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986081,0.00004636773,0.000005207884,0.0007386614,0.0000151075,0.0003548169,0.000006283674,0.00002897691,0.000196551],"genre_scores_gemma":[0.9997223,0.000004311469,0.000005871009,0.00001974903,0.00003378235,0.0001129115,0.00008952998,4.975757e-7,0.00001106343],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3262904,"threshold_uncertainty_score":0.7347905,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02746210465769972,"score_gpt":0.2663605205204918,"score_spread":0.238898415862792,"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."}}