{"id":"W2507973164","doi":"10.1086/686931","title":"<i>Representing Imperial Rivalry in the Early Modern Mediterranean</i>. Edited by Barbara Fuchs and Emily Weissbourd. Toronto: University of Toronto Press in association with the UCLA Center for Seventeenth- and Eighteenth-Century Studies and the William Andrews Clark Memorial Library, 2015. Pp. vi+282.","year":2016,"lang":"en","type":"article","venue":"Modern Philology","topic":"Global Maritime and Colonial Histories","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Rivalry; History; Classics; Art history; Library science; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009318836,0.0001607989,0.0003433238,0.000008382011,0.0004504372,0.00005875808,0.0003242496,0.0001771065,0.00001113464],"category_scores_gemma":[0.0001045101,0.00008648044,0.00004229925,0.00003828826,0.0008635093,0.0007173786,0.0002018317,0.000113215,1.295539e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001715153,"about_ca_system_score_gemma":0.00004910224,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01396093,"about_ca_topic_score_gemma":0.03983088,"domain_scores_codex":[0.9980203,0.0007893091,0.0002151464,0.0003202799,0.0003085697,0.0003464263],"domain_scores_gemma":[0.998678,0.0008302049,0.0002060117,0.0001625802,0.00007367481,0.00004949856],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.01592363,0.0004773401,0.1731124,0.0001407637,0.0008030078,0.00002236438,0.5439627,0.00000530128,0.0009207623,0.009667022,0.2349718,0.01999291],"study_design_scores_gemma":[0.03164085,0.001088379,0.03788027,0.0002733685,0.0005470679,0.00001111854,0.02203612,0.0005127075,0.00007896444,0.02977298,0.8752421,0.0009160956],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9273221,0.05174661,0.00004828827,0.01673663,0.0008423188,0.001254446,0.0001671027,0.00002568137,0.001856751],"genre_scores_gemma":[0.9755859,0.02344853,0.0000229506,0.0001829879,0.0005497741,0.00002371679,0.000007874214,0.00001025644,0.0001680484],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6402703,"threshold_uncertainty_score":0.9926052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00945653932412091,"score_gpt":0.242956274006738,"score_spread":0.2334997346826171,"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."}}