{"id":"W1428583425","doi":"10.1016/j.cropro.2015.08.019","title":"Structural equation modeling reveals complex relationships in mixed forage swards","year":2015,"lang":"en","type":"article","venue":"Crop Protection","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"Alberta Ministry of Agriculture and Forestry; University of Alberta; Saskatchewan Ministry of Agriculture","funders":"Natural Sciences and Engineering Research Council of Canada; University of Alberta","keywords":"Biology; Agronomy; Forb; Weed; Cirsium arvense; Perennial plant; Forage; Interspecific competition; Thistle; Legume; Biomass (ecology); Tussock; Competition (biology); Deserts and xeric shrublands; Vegetation (pathology); Noxious weed; Ecology; Grassland; Habitat","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":[0.002509243,0.0004138263,0.0004738568,0.0006388519,0.0006769007,0.001593361,0.0007117792,0.0006744353,0.002717367],"category_scores_gemma":[0.00873045,0.0004632101,0.0005915649,0.0009096191,0.0005098702,0.001010962,0.0007705938,0.0009088334,0.0002537598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001012628,"about_ca_system_score_gemma":0.0009286427,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03365292,"about_ca_topic_score_gemma":0.08648267,"domain_scores_codex":[0.9989185,0.0007070929,0.00003999541,0.000167546,0.00007080629,0.00009595406],"domain_scores_gemma":[0.9896471,0.008743579,0.0006914446,0.0003635004,0.0002518952,0.0003024599],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003027396,0.0003918773,0.9489604,0.00004221488,0.0008171808,0.000227007,0.003535627,0.01463223,0.001281039,0.009801719,0.0007015974,0.01930643],"study_design_scores_gemma":[0.0000438843,0.000191482,0.752543,0.00003600239,0.0003050977,0.0001427452,0.003360344,0.2297107,0.000345373,0.01212065,0.001169589,0.00003112424],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979177,0.00005169688,0.001656327,0.00008275094,0.000001789778,0.000003851556,0.0000421609,0.000005129669,0.0002384863],"genre_scores_gemma":[0.9984118,0.0000386806,0.001030532,0.00001486302,0.000002523016,0.000007736593,0.0001075221,0.000003782944,0.000382483],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03365292,"threshold_uncertainty_score":0.06691402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1519523451767038,"score_gpt":0.2878200850925497,"score_spread":0.1358677399158459,"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."}}