{"id":"W2946041163","doi":"10.1016/j.techfore.2019.05.005","title":"Digital technology, digital culture and the metric/nonmetric distinction","year":2019,"lang":"en","type":"article","venue":"Technological Forecasting and Social Change","topic":"University-Industry-Government Innovation Models","field":"Business, Management and Accounting","cited_by":69,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Obstacle; Metric (unit); Aside; Phenomenon; Digital transformation; Epistemology; Sociology; Transformation (genetics); Computer science; Mathematics; Philosophy; Linguistics; Political science; Economics; Law; Operations management; World Wide Web","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.004761543,0.0005507121,0.0005103528,0.003122132,0.001376611,0.009296876,0.0008181363,0.002129757,0.005585161],"category_scores_gemma":[0.01953747,0.0002716408,0.0003637877,0.004544287,0.01468229,0.01253883,0.00204072,0.002657641,0.0003218692],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004507713,"about_ca_system_score_gemma":0.002047477,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00453563,"about_ca_topic_score_gemma":0.004413536,"domain_scores_codex":[0.996667,0.002351493,0.000116042,0.000269965,0.0004491594,0.0001463475],"domain_scores_gemma":[0.974604,0.02082968,0.001962394,0.0008257715,0.001051922,0.000726248],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001039361,0.00001947313,0.001238852,0.0000201134,0.000005755023,0.00001370421,0.0003406342,0.0004929281,0.00002038956,0.9916654,0.000398207,0.00577404],"study_design_scores_gemma":[0.000008256464,0.00001582745,0.002340573,0.00004249449,0.000008090818,0.00003837414,0.0008313201,0.003340185,0.0000479993,0.9869588,0.006355945,0.00001217596],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2838215,0.03802122,0.1057006,0.08857941,0.001263141,0.00006453092,0.0003273121,0.0001223157,0.4821],"genre_scores_gemma":[0.9904603,0.002415199,0.00319049,0.0003844916,0.000304413,0.00002832206,0.00002333011,0.00002021295,0.003173359],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9986234,"threshold_uncertainty_score":0.03270584,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04523808100410318,"score_gpt":0.2143044679508202,"score_spread":0.169066386946717,"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."}}