{"id":"W4307571609","doi":"10.1007/s12206-022-1025-6","title":"Evaluation of design innovation using the length-time dimension and regression analysis","year":2022,"lang":"en","type":"article","venue":"Journal of Mechanical Science and Technology","topic":"Design Education and Practice","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Dimension (graph theory); Industrial engineering; Regression analysis; Computer science; Domain (mathematical analysis); Conceptual design; Product (mathematics); Variable (mathematics); Data mining; Engineering; Systems engineering; Machine learning; Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.009061738,0.00003728213,0.0001016976,0.0006828947,0.0001830358,0.00001335389,0.0001296551,0.00003211262,0.00003521625],"category_scores_gemma":[0.0009146897,0.0000246124,0.0000109296,0.003454409,0.00008653046,0.0001812856,0.00005574345,0.0001831885,1.639195e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008232224,"about_ca_system_score_gemma":0.0001321762,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001422659,"about_ca_topic_score_gemma":2.164585e-7,"domain_scores_codex":[0.9989052,0.0001287031,0.0002197696,0.00006563312,0.0006114637,0.00006919618],"domain_scores_gemma":[0.999016,0.0001057788,0.0001907504,0.00008383415,0.0005864467,0.00001720393],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001226331,0.00002560793,0.00004755904,0.000002067498,0.00005173722,7.156033e-7,0.0001108532,0.01096409,0.8778617,0.003093526,0.00008454191,0.1077453],"study_design_scores_gemma":[0.0002306085,0.0001934518,0.0002285815,0.000009486404,0.0004674322,0.0001382775,0.0007525369,0.920738,0.06588659,0.01096862,0.000332007,0.00005443278],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9704477,0.0004238882,0.02758111,0.001308613,0.0001270705,0.00007396503,2.678801e-7,0.00001409921,0.00002324878],"genre_scores_gemma":[0.9965473,0.00004497834,0.00337029,0.00002354714,0.000007737887,0.000001592805,8.358182e-8,0.000002531642,0.000001910694],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9097739,"threshold_uncertainty_score":0.3140635,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06572337311864211,"score_gpt":0.337641833562695,"score_spread":0.2719184604440529,"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."}}