{"id":"W6921928966","doi":"10.1139/cjps2010-035","title":"Structural equation modeling in the plant sciences: An example using yield components in oat","year":2011,"lang":"en","type":"article","venue":"BioOne Complete (BioOne)","topic":"Genetics and Plant Breeding","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Structural equation modeling; Path analysis (statistics); Seeding; Univariate; Latent variable; Plant density; Panicle; Yield (engineering); Variable (mathematics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":{"n_in":2,"stratum":"about_only","weight":3321.24,"opus":{"tier":"T1","genre":"conceptual","about_ca":false,"confidence":"medium","reason":"Tutorial introducing plant scientists to structural equation modeling, reviewing its principles and offering guidelines on when it is appropriate; the oat field trial is an illustrative vehicle and the object is statistical practice in a research community."},"gpt":{"tier":"OUT","genre":"empirical","about_ca":false,"confidence":"high","reason":"Structural equation modeling is used to analyze oat yield, so the method is not the object of study."},"grok":{"tier":"T1","genre":"empirical","about_ca":false,"confidence":"medium","reason":"Primary aim is introducing SEM as statistical practice for plant scientists, with guidelines on when SEM is appropriate."}},"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01545305,0.0007139158,0.001004856,0.001612879,0.001017406,0.00178879,0.000989593,0.001405373,0.002430968],"category_scores_gemma":[0.01733316,0.0002911357,0.002035278,0.00719122,0.0009217116,0.001427925,0.001444464,0.002566873,0.0003278083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003015741,"about_ca_system_score_gemma":0.001733187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06202038,"about_ca_topic_score_gemma":0.09641036,"domain_scores_codex":[0.9924557,0.006441313,0.0002342544,0.00019156,0.0005906505,0.00008653726],"domain_scores_gemma":[0.9738964,0.02352024,0.0004740634,0.0005588603,0.001402545,0.0001479146],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000468112,0.001280981,0.1005574,0.002386161,0.001502103,0.002257985,0.009654765,0.2151976,0.002257639,0.1766047,0.02664527,0.4611873],"study_design_scores_gemma":[0.000456541,0.001080666,0.07488064,0.001101204,0.0006722395,0.0004327665,0.005136461,0.607181,0.002370276,0.206768,0.09961074,0.0003094887],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4621075,0.01688928,0.4649699,0.02465406,0.0006977877,0.001072041,0.002961286,0.0006565898,0.02599155],"genre_scores_gemma":[0.5223335,0.01011277,0.458073,0.001267781,0.0002096311,0.0005478522,0.001330189,0.0001828909,0.005942353],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06202038,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9152969241539349,"score_gpt":0.2648278698154878,"score_spread":0.650469054338447,"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."}}