{"id":"W2908520353","doi":"10.1353/vpr.2018.0049","title":"Between Counterfeit Coin and Genuine Article: From Copying to Originality in Tit-Bits","year":2018,"lang":"en","type":"article","venue":"Victorian periodicals review","topic":"American History and Culture","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Copying; Counterfeit; Reprint; Nothing; Originality; Computer science; George (robot); Competitor analysis; Law and economics; Sociology; Law; Epistemology; Philosophy; Business; Political science; Artificial intelligence; Social science; Marketing","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":[0.008878968,0.0001854375,0.0002853147,0.002686027,0.004769764,0.01158797,0.0007806579,0.003158024,0.004074709],"category_scores_gemma":[0.04859289,0.0003595522,0.0002246251,0.004613033,0.03784681,0.01229611,0.003743702,0.005540966,0.00066333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006207393,"about_ca_system_score_gemma":0.007236041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01049128,"about_ca_topic_score_gemma":0.01617427,"domain_scores_codex":[0.9861668,0.006282299,0.0009514314,0.0008247116,0.004857877,0.0009169079],"domain_scores_gemma":[0.9685453,0.02352666,0.002614832,0.001636866,0.003121391,0.000555073],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002656195,0.00001205026,0.0008560818,0.0003308062,0.000008787834,0.0004688786,0.01492299,0.00005903945,0.0001528882,0.9031776,0.03297191,0.04701231],"study_design_scores_gemma":[0.000009599474,0.00003160649,0.003721507,0.001836303,0.00001927171,0.0009630973,0.01311028,0.0001072246,0.0005789635,0.1721104,0.8074744,0.00003723345],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.04987391,0.3377301,0.00292226,0.1591055,0.009145795,0.00004208357,0.00004602604,0.00004374167,0.4410906],"genre_scores_gemma":[0.772285,0.1234251,0.001161951,0.04291357,0.006850434,0.0000590501,0.00004046732,0.0001132131,0.05315127],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01158797,"threshold_uncertainty_score":0.04695702,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01784030228690615,"score_gpt":0.2690757609432124,"score_spread":0.2512354586563063,"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."}}