{"id":"W3035104747","doi":"10.15173/jpc.v6i1.4348","title":"The mathematical corporation: Where machine intelligence and human ingenuity achieve the impossible","year":2020,"lang":"en","type":"article","venue":"Journal of Professional Communication","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ingenuity; Corporation; Negotiation; Professional communication; Power (physics); Public relations; Management; Sociology; Engineering ethics; Political science; Engineering; Law; Economics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001271052,0.0001037941,0.0001356029,0.00003424652,0.001060343,0.0003429185,0.0009828786,0.00005058697,0.0001126996],"category_scores_gemma":[0.0003174966,0.00005124127,0.00004849153,0.0002765126,0.0002216581,0.0009933467,0.0005708456,0.0005341595,0.00003348545],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001383341,"about_ca_system_score_gemma":0.00004010981,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003079177,"about_ca_topic_score_gemma":0.00007457492,"domain_scores_codex":[0.9988815,0.00008028375,0.0005081854,0.00008403553,0.00033978,0.000106236],"domain_scores_gemma":[0.998211,0.0002864918,0.0007753438,0.0003234409,0.000384956,0.00001874074],"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":[0.0004072192,0.0002775257,0.0106449,0.0003378921,0.00008164352,0.000004681574,0.001176459,0.00007772316,0.001851966,0.8965991,0.02798401,0.06055691],"study_design_scores_gemma":[0.0006159682,0.0001650232,0.0323681,0.001145838,0.0002322322,0.0001046782,0.005623212,0.02617476,0.0007315023,0.5952705,0.3370262,0.0005419643],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.308825,0.01701558,0.05051102,0.6105462,0.00136918,0.001309818,0.00001315276,0.0001089214,0.01030113],"genre_scores_gemma":[0.9973642,0.0003945108,0.0004378554,0.001226425,0.000430746,0.000005286059,0.00001014715,0.000009277154,0.00012155],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6885392,"threshold_uncertainty_score":0.8155405,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.110365608589652,"score_gpt":0.3451583471656725,"score_spread":0.2347927385760205,"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."}}