{"id":"W4401690668","doi":"10.1016/j.heliyon.2024.e36272","title":"Enhancing image caption generation through context-aware attention mechanism","year":2024,"lang":"en","type":"article","venue":"Heliyon","topic":"Multimodal Machine Learning Applications","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Athabasca University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Context (archaeology); Mechanism (biology); Image (mathematics); Psychology; Computer science; Computer vision; History; Epistemology; Philosophy","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007202523,0.002312375,0.000816183,0.001557433,0.0006803553,0.001388122,0.00135836,0.001381062,0.0093676],"category_scores_gemma":[0.003523367,0.0003359221,0.0007659989,0.001145187,0.0003475598,0.001964314,0.001238324,0.001500392,0.006926108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000698689,"about_ca_system_score_gemma":0.000869901,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007309279,"about_ca_topic_score_gemma":0.01152603,"domain_scores_codex":[0.9993759,0.0001201011,0.00003470944,0.0002433612,0.0001588148,0.00006726097],"domain_scores_gemma":[0.9990501,0.0002289041,0.00006012136,0.0002176111,0.0003746571,0.00006861067],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007544017,0.0003535385,0.0009702428,0.0009154393,0.0002222349,0.000566994,0.0001325448,0.02180113,0.1501617,0.001964353,0.09865199,0.7235054],"study_design_scores_gemma":[0.0001511637,0.0004246018,0.003408302,0.0000941789,0.000254901,0.0009444238,0.0001442956,0.6584399,0.2781099,0.00279672,0.05507594,0.0001556674],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08316045,0.01366603,0.7109622,0.001762484,0.005059758,0.001316055,0.007460592,0.1286882,0.04792414],"genre_scores_gemma":[0.4063702,0.004580615,0.5285718,0.001441058,0.001259775,0.0005377126,0.02201059,0.002272395,0.03295587],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0093676,"threshold_uncertainty_score":0.0313378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02157788872882548,"score_gpt":0.2942668051284159,"score_spread":0.2726889163995904,"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."}}