{"id":"W1963866613","doi":"10.12735/jbm.v2i4p01","title":"From Acting What’s next to Speeding Trap: Co-Evolutionary Dynamics of an Emerging Technology-Leader","year":2013,"lang":"en","type":"article","venue":"Journal of Business & Management","topic":"Innovation and Knowledge Management","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Trap (plumbing); Dynamics (music); Evolutionary dynamics; Computer science; Physics; Sociology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003701162,0.0001957006,0.0002531875,0.001646552,0.004651444,0.00547789,0.0009350099,0.001492353,0.002366025],"category_scores_gemma":[0.008783097,0.0001986892,0.0002971854,0.0008266022,0.005386213,0.004416971,0.004416734,0.00131284,0.0003231582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002143249,"about_ca_system_score_gemma":0.002843541,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003381812,"about_ca_topic_score_gemma":0.003936697,"domain_scores_codex":[0.997315,0.001413574,0.00006657261,0.0003400725,0.0003624448,0.0005022632],"domain_scores_gemma":[0.9933636,0.002326083,0.001343573,0.000475057,0.0009636602,0.001528029],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002443211,0.0006300623,0.2905407,0.0001351642,0.000102824,0.007136016,0.3683639,0.005036695,0.007054735,0.2371281,0.003431483,0.08019589],"study_design_scores_gemma":[0.00008141562,0.0006642248,0.1379777,0.000259944,0.00009332959,0.002729397,0.5942969,0.04246565,0.003488839,0.1533389,0.06436305,0.0002407009],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9781325,0.00009547079,0.005949435,0.0022884,0.00001690765,0.0000317673,0.00001213126,0.00001790191,0.01345556],"genre_scores_gemma":[0.9983863,0.00002771696,0.0008095257,0.00006386868,0.00000345395,0.000009018148,0.000006754306,0.000003510758,0.0006898673],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00547789,"threshold_uncertainty_score":0.01957387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02756233678191996,"score_gpt":0.2620150291089386,"score_spread":0.2344526923270187,"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."}}