{"id":"W3034614833","doi":"","title":"Using IIIF to Teach Rare Books and Special Collections","year":2018,"lang":"en","type":"article","venue":"TSpace","topic":"Library Collection Development and Digital Resources","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Special collections; Special section; Linguistics; History; Computer science; Library science; Philosophy; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008204319,0.0003865657,0.000256881,0.001547594,0.001693216,0.003410459,0.0009828677,0.0004550744,0.04673199],"category_scores_gemma":[0.002360204,0.0002496037,0.000372801,0.001223488,0.0007082938,0.001985228,0.002843299,0.0009153543,0.01446565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002521008,"about_ca_system_score_gemma":0.003353139,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007542111,"about_ca_topic_score_gemma":0.03798849,"domain_scores_codex":[0.9995678,0.00005997746,0.0000158236,0.00009793465,0.0001516561,0.0001067757],"domain_scores_gemma":[0.9980963,0.000354951,0.00008481191,0.0002651046,0.0001942042,0.001004629],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001340154,0.0006668596,0.007518644,0.000418224,0.00001416199,0.0009418811,0.01501772,0.001274761,0.01696948,0.01499972,0.1599107,0.7821338],"study_design_scores_gemma":[0.00003109826,0.0001756932,0.009515853,0.0001787827,0.00001032225,0.0007155066,0.004121339,0.001175102,0.009756181,0.003878897,0.9703968,0.00004442952],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2164671,0.00118505,0.1417331,0.004714846,0.0008746634,0.0009353018,0.004463615,0.03250379,0.5971224],"genre_scores_gemma":[0.3739001,0.001789248,0.2703318,0.0009670175,0.0002598084,0.0005039841,0.004993611,0.004278614,0.3429758],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04673199,"threshold_uncertainty_score":0.156334,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03925939823470127,"score_gpt":0.2906443395008088,"score_spread":0.2513849412661076,"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."}}