{"id":"W2899381446","doi":"10.1115/detc2018-85516","title":"TRIZ Application in Bionic Modeling for Lightweight Design of Machine Tool Column","year":2018,"lang":"en","type":"article","venue":"","topic":"Design Education and Practice","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"TRIZ; Table (database); Computer science; Selection (genetic algorithm); Engineering drawing; Engineering; Artificial intelligence; Data mining","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":[0.0002995442,0.00005555266,0.00007973377,0.00007864168,0.00001656529,0.00001076137,0.00006966094,0.00004266145,0.00009744667],"category_scores_gemma":[0.00004149426,0.00005506936,0.00001637246,0.0001711301,0.000007813917,0.0001211075,0.000003776537,0.00003903523,0.00004357453],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003123074,"about_ca_system_score_gemma":0.00002488877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002892826,"about_ca_topic_score_gemma":0.00002774703,"domain_scores_codex":[0.9995687,0.00001686053,0.0001889544,0.00008455746,0.00004790742,0.0000930012],"domain_scores_gemma":[0.9996518,0.0001208065,0.00002280784,0.0001286196,0.000056744,0.00001918574],"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":[0.0005046992,0.000603482,0.0005019419,0.0004472361,0.0001295958,4.201218e-7,0.002801261,0.4684835,0.2617338,0.03964438,0.02196669,0.2031829],"study_design_scores_gemma":[0.0002552513,0.0000359001,0.00002807653,0.000005531228,0.000006863937,6.998368e-7,0.00002299651,0.9753065,0.01421231,0.0006416014,0.009412476,0.00007185652],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006293589,0.00009657388,0.9890267,0.0001248504,0.0001187237,0.0004202352,0.000002243051,0.00006979172,0.003847328],"genre_scores_gemma":[0.9550304,0.00003173821,0.04417437,0.00005153491,0.00006680936,0.0001015121,0.0000072968,0.00001413521,0.0005222016],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9487368,"threshold_uncertainty_score":0.2245663,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0315844946843287,"score_gpt":0.2787335697374052,"score_spread":0.2471490750530765,"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."}}