{"id":"W4387023718","doi":"10.1515/pdtc-2023-0017","title":"Content Analysis of Libraries’ Instagram Posts: Cultural Collection, Activities, and Preservation of Cultural Heritage","year":2023,"lang":"en","type":"article","venue":"Preservation Digital Technology & Culture","topic":"Web and Library Services","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cultural heritage; Social media; Sustainability; Sociology; Public relations; Media studies; Political 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":[0.00008458126,0.0001971633,0.0003977396,0.0006482704,0.0001336142,0.0003273233,0.0008288198,0.0002672579,0.000009948706],"category_scores_gemma":[0.0001679177,0.0001549299,0.0001157059,0.006963996,0.0002259586,0.01105039,0.0006259509,0.000174428,0.000001779191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002068421,"about_ca_system_score_gemma":0.00004453075,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006617406,"about_ca_topic_score_gemma":0.00004758139,"domain_scores_codex":[0.9985586,0.00003436335,0.0004666828,0.0004025176,0.0003053148,0.000232481],"domain_scores_gemma":[0.9987174,0.00006575865,0.0003578289,0.0004596576,0.0003474463,0.00005192284],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001147841,0.0003121158,0.6044417,0.0002980116,0.001968544,0.000006879276,0.01628158,0.0004683085,0.02762739,0.3317094,0.01109679,0.005674546],"study_design_scores_gemma":[0.002110682,0.00102355,0.7434157,0.0001937536,0.0003970592,0.00001981527,0.03249975,0.08217234,0.05586785,0.03510254,0.04607539,0.001121557],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922229,0.0003590789,0.0008633522,0.003599736,0.00007828409,0.0003127694,0.00009779107,0.0007022049,0.001763861],"genre_scores_gemma":[0.9944492,0.0001345056,0.001786101,0.00008802325,0.00001533509,0.00004268865,0.0004004977,0.000008612265,0.003075019],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2966068,"threshold_uncertainty_score":0.8011268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03246995895969679,"score_gpt":0.2457484585942991,"score_spread":0.2132784996346023,"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."}}