{"id":"W4280568637","doi":"10.1007/s00163-022-00389-w","title":"Organizing the fragmented landscape of multidisciplinary product development: a mapping of approaches, processes, methods and tools from the scientific literature","year":2022,"lang":"en","type":"article","venue":"Research in Engineering Design","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"Fonds Unique Interministériel","keywords":"Variety (cybernetics); Multidisciplinary approach; New product development; Computer science; Identification (biology); Product (mathematics); Process (computing); Product engineering; Data science; Product design; Mechatronics; Systems engineering; Management science; Engineering; Knowledge management; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.01044819,0.001106607,0.001123511,0.05965049,0.003174251,0.01553411,0.001658473,0.002041192,0.002670061],"category_scores_gemma":[0.01192436,0.0007567317,0.001004229,0.05494234,0.006060635,0.01858298,0.005086432,0.00220957,0.000617293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007016904,"about_ca_system_score_gemma":0.009937461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004591492,"about_ca_topic_score_gemma":0.005770631,"domain_scores_codex":[0.991384,0.003405644,0.0008607598,0.0007781145,0.003093704,0.0004778474],"domain_scores_gemma":[0.9788409,0.01348455,0.001571044,0.0008903692,0.004757468,0.000455595],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001110736,0.0002098989,0.009055385,0.01436865,0.0001976099,0.002135537,0.05069008,0.002740199,0.003180715,0.2086708,0.009520615,0.6991194],"study_design_scores_gemma":[0.00003127695,0.0001876334,0.028993,0.04685187,0.0003130704,0.002866455,0.19231,0.004659612,0.002199934,0.1837883,0.5375968,0.0002021074],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.1369343,0.6426102,0.1001269,0.0334482,0.000922912,0.0007340573,0.0009070698,0.0002860907,0.08403029],"genre_scores_gemma":[0.4438369,0.4208863,0.1248099,0.003150175,0.000436821,0.0006390497,0.001155046,0.0001507459,0.004935103],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9403495,"threshold_uncertainty_score":0.05525595,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.163517560871185,"score_gpt":0.3164604415172891,"score_spread":0.1529428806461041,"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."}}