{"id":"W2906942591","doi":"10.1016/j.ijis.2018.11.001","title":"Harnessing the potential of additive manufacturing technologies: Challenges and opportunities for entrepreneurial strategies","year":2018,"lang":"en","type":"article","venue":"International Journal of Innovation Studies","topic":"Cultural Industries and Urban Development","field":"Social Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Transformative learning; Exploit; Entrepreneurship; China; Production (economics); Business; Industrial organization; Marketing; Knowledge management; Economic geography; Political science; Economics; Sociology; Computer science","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":[0.0005460913,0.00005835544,0.000117449,0.0001358993,0.000223923,0.00007179817,0.0001771319,0.00003768303,0.00001301331],"category_scores_gemma":[0.0005194636,0.00003687109,0.00002514612,0.00005966412,0.0006388887,0.0003263401,0.0000678174,0.00006571643,1.168306e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004668723,"about_ca_system_score_gemma":0.0001297165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001079559,"about_ca_topic_score_gemma":0.00003915856,"domain_scores_codex":[0.9991599,0.0000284959,0.000374726,0.00006021205,0.0003000176,0.0000765971],"domain_scores_gemma":[0.9963639,0.0001575675,0.0005355547,0.00002845808,0.002907555,0.000006919226],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001596514,0.00002568759,0.00003564951,0.00001183558,0.0006821135,0.000006905084,0.02236766,0.000005908606,0.0005404468,0.1155565,0.01389988,0.8467078],"study_design_scores_gemma":[0.0004158419,0.0001203462,0.001097382,0.00016387,0.00002475349,0.00001336349,0.6859844,0.000003049575,0.01313437,0.02808344,0.2708775,0.00008162455],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8314393,0.005172851,0.002072063,0.1532601,0.00416824,0.0002842947,0.0000358345,0.00004156518,0.003525776],"genre_scores_gemma":[0.9911317,0.007404502,0.0002605169,0.00006420473,0.0007626757,0.000004860497,0.000001383752,0.000002440538,0.0003676983],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8466261,"threshold_uncertainty_score":0.2354012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1945070369314538,"score_gpt":0.3742221161300764,"score_spread":0.1797150791986226,"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."}}