{"id":"W4288060708","doi":"10.18357/kula.232","title":"Modelling Linked Data for Conservation","year":2022,"lang":"en","type":"article","venue":"KULA knowledge creation dissemination and preservation studies","topic":"Conservation Techniques and Studies","field":"Arts and Humanities","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Arts and Humanities Research Council","keywords":"Documentation; Metadata; Computer science; Materiality (auditing); Scope (computer science); Event (particle physics); Object (grammar); Data science; Descriptive statistics; Information retrieval; World Wide Web; Artificial intelligence","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.0009834475,0.0001834731,0.0002622757,0.0002102501,0.002278363,0.000170097,0.0002528179,0.00003049605,0.0002707537],"category_scores_gemma":[0.0005086192,0.000183992,0.00004804978,0.000146927,0.0001719313,0.0006757728,0.0004573544,0.0001068556,0.000003200872],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007924499,"about_ca_system_score_gemma":0.00004048353,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007405668,"about_ca_topic_score_gemma":0.0002908939,"domain_scores_codex":[0.9985726,0.0001169395,0.0004796065,0.0004265682,0.0002361557,0.0001680823],"domain_scores_gemma":[0.9973757,0.0009213215,0.0002497283,0.000368611,0.001048904,0.00003576078],"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":[0.0001236268,0.0001941123,0.0012703,0.0002815917,0.0002262091,2.555122e-7,0.1429767,0.0004006739,0.0000662138,0.5594499,0.2807361,0.01427431],"study_design_scores_gemma":[0.0003209865,0.00005924108,0.0002777181,0.00003189828,0.0000658038,7.605968e-7,0.01679377,0.1908528,0.00002040467,0.007714089,0.7836716,0.0001909223],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2978074,0.0653943,0.1840395,0.1202196,0.006222103,0.01344371,0.00525676,0.003532534,0.304084],"genre_scores_gemma":[0.7803518,0.001446465,0.002561897,0.0006768318,0.0006275389,0.002595061,0.00450756,0.00005618514,0.2071766],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5517358,"threshold_uncertainty_score":0.9990205,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2675866510265349,"score_gpt":0.3974303436591974,"score_spread":0.1298436926326624,"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."}}