{"id":"W4405960131","doi":"10.1093/geroni/igae098.1586","title":"ASSESSING AGE INCLUSIVITY USING THE AGE-FRIENDLY INVENTORY AND CAMPUS CLIMATE SURVEY","year":2024,"lang":"en","type":"article","venue":"Innovation in Aging","topic":"Retirement, Disability, and Employment","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geography; Environmental science; Psychology","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":[0.00844865,0.0002508472,0.0002761948,0.002396159,0.0009148925,0.001585257,0.0005285285,0.0003697759,0.001731715],"category_scores_gemma":[0.01777449,0.0001995584,0.0004902815,0.00120018,0.0003702577,0.001246002,0.002537863,0.0008415502,0.0004452365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008143359,"about_ca_system_score_gemma":0.001372058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005699037,"about_ca_topic_score_gemma":0.01001313,"domain_scores_codex":[0.9956545,0.002099684,0.0005521048,0.0001717415,0.001173752,0.000348253],"domain_scores_gemma":[0.9822735,0.003652408,0.005712952,0.001042281,0.005067736,0.002251151],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002905438,0.0001721664,0.9680438,0.00004376922,0.00003029871,0.00004628642,0.004008901,0.0001090067,0.0003102499,0.0001327165,0.001322905,0.02575077],"study_design_scores_gemma":[0.000004015742,0.0003576274,0.9806215,0.00009184681,0.00001439316,0.0001156466,0.0129192,0.0005193347,0.0006641606,0.0001641272,0.00449937,0.00002873705],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9925115,0.0001307382,0.001561437,0.0002793875,0.00003361562,0.0001797477,0.0003223167,0.0000521251,0.0049292],"genre_scores_gemma":[0.9951177,0.0001905667,0.003230732,0.0001466614,0.00001606769,0.000238996,0.0003084037,0.000008170073,0.0007428324],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00844865,"threshold_uncertainty_score":0.04468125,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2697840003141523,"score_gpt":0.4779657198318633,"score_spread":0.208181719517711,"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."}}