{"id":"W7164841587","doi":"10.22271/maths.2025.v10.i1c.2392","title":"Resolving design of experiments for factorial layouts with applications to fraser valley dairy farm productivity","year":2025,"lang":"","type":"article","venue":"International Journal of Statistics and Applied Mathematics","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Fractional factorial design; Factorial experiment; Productivity; Matching (statistics); Factorial; Matrix (chemical analysis); Linear programming; Moment (physics); Function (biology); Weibull distribution","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.06366202,0.003309206,0.004269718,0.002729001,0.001690911,0.004078988,0.004167721,0.003498789,0.007914462],"category_scores_gemma":[0.1786186,0.002908167,0.005202999,0.003831526,0.004506681,0.002565666,0.004873035,0.006262173,0.0008889786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005315003,"about_ca_system_score_gemma":0.006012774,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005858305,"about_ca_topic_score_gemma":0.008380116,"domain_scores_codex":[0.9425268,0.04702385,0.001472402,0.004732046,0.003516556,0.0007282454],"domain_scores_gemma":[0.6981637,0.2806788,0.00906534,0.00740755,0.003481756,0.001202906],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00124583,0.0004156541,0.009937105,0.002698506,0.00136352,0.0005353368,0.001490001,0.6317223,0.004381754,0.1591885,0.006261503,0.1807599],"study_design_scores_gemma":[0.0007084404,0.0007144787,0.002357427,0.0002544254,0.0002090258,0.0001174955,0.0001422149,0.7341025,0.00162351,0.2460263,0.01363686,0.0001073303],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005319885,0.001626829,0.9900074,0.0005051973,0.00008502242,0.000359865,0.000479591,0.0007064209,0.0009097926],"genre_scores_gemma":[0.05649626,0.0007279118,0.9386525,0.0003885878,0.0001681442,0.002091448,0.0006795931,0.0003016899,0.0004939536],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9941417,"threshold_uncertainty_score":0.3366809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1032006295531062,"score_gpt":0.4307671494266128,"score_spread":0.3275665198735066,"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."}}