{"id":"W1979760414","doi":"10.1108/17542731111139509","title":"Statistical, technical and sociological dimensions of design of experiments","year":2011,"lang":"en","type":"article","venue":"The TQM Journal","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"JDA Software (Canada)","funders":"","keywords":"Originality; Computer science; Relation (database); Value (mathematics); Management science; Interpretation (philosophy); Design of experiments; Operations research; Risk analysis (engineering); Sociology; Business; Economics; Engineering; Social science; Data mining; Statistics; Mathematics; Machine learning; Qualitative research","routes":{"ca_aff":true,"ca_fund":false,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005915818,0.0001013844,0.0003278335,0.00008502223,0.0001497759,0.00002635417,0.000589441,0.00007271856,0.001150066],"category_scores_gemma":[0.002146756,0.00004394452,0.00007111573,0.0001670091,0.001040804,0.0001056576,0.0002156332,0.0002475666,0.00001764696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001548421,"about_ca_system_score_gemma":0.00005226331,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005667104,"about_ca_topic_score_gemma":5.964375e-8,"domain_scores_codex":[0.9968413,0.001366601,0.0007244626,0.0001677669,0.0007195334,0.0001803972],"domain_scores_gemma":[0.9963007,0.002765786,0.000362809,0.0002861473,0.0001548053,0.0001297455],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006696782,0.0004690998,0.002694176,0.00000196031,0.00005457894,0.00002905559,0.003715632,0.00005123285,0.9595975,0.01876687,0.004298612,0.009651574],"study_design_scores_gemma":[0.001338694,0.003547353,0.05918127,0.00005268495,0.00008274162,0.0009307916,0.006079593,0.001595828,0.369652,0.5569673,0.0002436107,0.0003282237],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2658953,0.001010952,0.7299408,0.0001059128,0.0001891712,0.0002276252,0.000009012667,0.00001187965,0.002609298],"genre_scores_gemma":[0.6421928,0.00005204287,0.3576615,0.00003481876,0.00001435738,0.000002217968,5.48895e-8,0.000004313349,0.00003780566],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5899456,"threshold_uncertainty_score":0.999763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5071897920712852,"score_gpt":0.4986354264586207,"score_spread":0.008554365612664538,"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."}}