{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.01916281,0.001160351,0.001113557,0.009469688,0.003497504,0.01659585,0.00544121,0.004858623,0.01326135],"category_scores_gemma":[0.07179736,0.001323037,0.00480294,0.01416069,0.003622534,0.0238161,0.01050907,0.004699121,0.003933759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007305395,"about_ca_system_score_gemma":0.006227873,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03886207,"about_ca_topic_score_gemma":0.02827662,"domain_scores_codex":[0.9819242,0.008061685,0.002097529,0.002686319,0.004563822,0.0006664303],"domain_scores_gemma":[0.9572555,0.02586151,0.001995937,0.008819894,0.005278894,0.0007881925],"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":[0.00007203779,0.00008700312,0.002587552,0.0004185587,0.0001114975,0.0005034044,0.001739735,0.06191466,0.0002804526,0.8627496,0.01789359,0.05164186],"study_design_scores_gemma":[0.00004408591,0.00003502956,0.0004239266,0.0006598634,0.0000731947,0.000340305,0.0007514642,0.1824142,0.0008033091,0.5266812,0.2877026,0.0000707954],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004655331,0.001781363,0.9487389,0.007012366,0.0005178883,0.0007352833,0.008532104,0.003648767,0.02437792],"genre_scores_gemma":[0.1042325,0.003744377,0.8412999,0.001522574,0.000328897,0.001732949,0.03032897,0.001529038,0.01528087],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9834042,"threshold_uncertainty_score":0.1013438,"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."}}