{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002475354,0.0001285502,0.00009672497,0.00008707286,0.0001983922,0.0003886145,0.0002575388,0.00007559515,0.00004887811],"category_scores_gemma":[0.00002616798,0.0001275376,0.00006749846,0.0003045878,0.00001517961,0.0008728537,0.00009340628,0.0002050445,0.001123786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000100271,"about_ca_system_score_gemma":0.00004262493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001950571,"about_ca_topic_score_gemma":0.00008321204,"domain_scores_codex":[0.9988067,0.00007989195,0.0002172659,0.0004722674,0.0002333992,0.000190468],"domain_scores_gemma":[0.9994009,0.0000460965,0.00005172454,0.0003788037,0.00007995896,0.00004249698],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[8.120974e-7,0.00002205298,0.00002243092,0.0001263678,0.00001093329,0.000007453294,0.0008750428,0.00009758176,0.6625952,0.3155994,0.0001597309,0.02048298],"study_design_scores_gemma":[0.0002121912,0.00006836333,0.001749957,0.0003362746,0.00002065138,0.00004219323,0.0000749051,0.8579504,0.1256452,0.009463986,0.004089203,0.0003466019],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07115507,0.0006030859,0.9237899,0.002417082,0.0006332528,0.0002144382,0.000003340868,0.0007272855,0.0004565658],"genre_scores_gemma":[0.9491285,0.00009999365,0.04968255,0.0002872926,0.0003083796,0.00008537807,0.00003906436,0.00001854377,0.000350315],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8779734,"threshold_uncertainty_score":0.9996539,"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."}}