{"id":"W3036683378","doi":"10.33137/rr.v43i1.34091","title":"Wilkinson, Hazel, principal investigator. Fleuron: A Database of Eighteenth-Century Printers’ Ornaments","year":2020,"lang":"en","type":"article","venue":"Renaissance and Reformation","topic":"Cultural Heritage Materials Analysis","field":"Arts and Humanities","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ornaments; Principal (computer security); Art; History; Database; Ancient history; Archaeology; Visual arts; Computer science; Computer security","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":[0.004443365,0.0006143264,0.0006937856,0.007614977,0.0011399,0.00382394,0.001051494,0.0008003169,0.2309783],"category_scores_gemma":[0.02917806,0.0005541315,0.0002859563,0.0161823,0.0003809861,0.002475332,0.001750344,0.001446933,0.1181839],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001252909,"about_ca_system_score_gemma":0.004387331,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01071762,"about_ca_topic_score_gemma":0.02246674,"domain_scores_codex":[0.9958734,0.0005850309,0.0005271315,0.0004845939,0.002252609,0.0002772122],"domain_scores_gemma":[0.9616798,0.009062543,0.004664735,0.002008943,0.01954331,0.003040557],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001185011,0.00001803358,0.002941496,0.0001995214,0.000006527142,0.00002844914,0.0001473845,0.00001914394,0.00006352824,0.0002890973,0.9348341,0.06133416],"study_design_scores_gemma":[0.0000392683,0.00001502883,0.01316366,0.0003019191,0.00001339466,0.00005347894,0.0005006316,0.00004403666,0.0001547872,0.0002091556,0.9854913,0.00001341601],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.01364567,0.0236723,0.004161596,0.02597732,0.003508331,0.001041102,0.6729967,0.002940918,0.2520561],"genre_scores_gemma":[0.04384029,0.02486177,0.009082424,0.003593359,0.001528361,0.001812055,0.2750919,0.002215991,0.6379738],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2309783,"threshold_uncertainty_score":0.7726994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04317527081736023,"score_gpt":0.2284135705903376,"score_spread":0.1852382997729773,"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."}}