{"id":"W4385784741","doi":"10.1007/978-3-319-08234-9_501-1","title":"Automated Image Captioning for the Visually Impaired","year":2023,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Computer Graphics and Games","topic":"Multimodal Machine Learning Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"CNIB Foundation; Ontario Tech University","funders":"","keywords":"Closed captioning; Visually impaired; Computer science; Computer vision; Image (mathematics); Artificial intelligence; Human–computer interaction","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004082728,0.0003254369,0.0003885675,0.0002774724,0.0002672199,0.0001756204,0.0009190299,0.0001941151,0.000004088888],"category_scores_gemma":[0.00003349067,0.000256776,0.0002253126,0.0001367897,0.0002021808,0.00012665,0.0004582074,0.0003528,0.00001280241],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001035876,"about_ca_system_score_gemma":0.00008351562,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009671105,"about_ca_topic_score_gemma":0.00001453392,"domain_scores_codex":[0.9984253,0.0000263531,0.0004613334,0.0005434258,0.0002966815,0.0002469103],"domain_scores_gemma":[0.9974531,0.001128666,0.0003909765,0.0007030249,0.0002380046,0.00008624883],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004106312,0.00001484091,0.00009641888,0.00009655842,0.0001394626,0.000003010761,0.0004888374,0.0002186043,0.000004450052,0.9547811,0.004058357,0.04009422],"study_design_scores_gemma":[0.0003119592,0.0001789574,0.0150034,0.0001456485,0.00006982198,0.000009624128,0.000003181296,0.848282,0.000001822455,0.06730237,0.06830741,0.0003837933],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0004332911,0.0008475563,0.9662374,0.002828037,0.001028918,0.001409661,0.00008426911,0.001830141,0.02530076],"genre_scores_gemma":[0.07323427,0.02197263,0.7535737,0.002182635,0.003838189,0.001084527,0.0004946248,0.0008011142,0.1428184],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8874788,"threshold_uncertainty_score":0.9999884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01395764660038844,"score_gpt":0.2692701808536056,"score_spread":0.2553125342532171,"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."}}