{"id":"W4225408468","doi":"10.1007/s11042-022-12914-z","title":"Dataset and semantic based-approach for image sonification","year":2022,"lang":"en","type":"article","venue":"Multimedia Tools and Applications","topic":"Tactile and Sensory Interactions","field":"Neuroscience","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Computer Research Institute of Montréal","funders":"","keywords":"Computer science; Sonification; Image (mathematics); Artificial intelligence; Natural language processing; Computer vision; Information retrieval; 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":[],"consensus_categories":[],"category_scores_codex":[0.00005128718,0.00007844416,0.00007921582,0.00005212481,0.000715164,0.00009261744,0.0001067778,0.00001811879,0.0000665426],"category_scores_gemma":[0.00008176496,0.00008003509,0.0000215138,0.0001200733,0.00007604658,0.0001655804,0.00005235522,0.0001104349,0.000009693393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001470452,"about_ca_system_score_gemma":0.00001790975,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001242036,"about_ca_topic_score_gemma":0.000001528037,"domain_scores_codex":[0.9992696,0.00003433123,0.0001284818,0.0003466542,0.00009259303,0.0001283241],"domain_scores_gemma":[0.9991914,0.0004296961,0.00006128688,0.000237606,0.00001570941,0.00006429833],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005678566,0.0007768766,0.0001899743,0.00009500144,0.00000984797,0.000001867853,0.0003784393,0.0004501704,0.8851511,0.006362736,0.0223403,0.08418692],"study_design_scores_gemma":[0.0006469408,0.00005803984,0.0007753882,0.000001710368,0.00004004237,0.00004433151,0.0005065906,0.2747097,0.03374745,0.0003094189,0.6889337,0.0002266828],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08539284,0.0001314488,0.784414,0.009429821,0.0003125574,0.009691726,0.1057834,0.0004147636,0.004429455],"genre_scores_gemma":[0.9711033,0.00003509468,0.01766832,0.001006365,0.0001027116,0.005520524,0.004198063,0.00002048897,0.000345145],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8857104,"threshold_uncertainty_score":0.5500535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06610190023846174,"score_gpt":0.3110084806871411,"score_spread":0.2449065804486794,"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."}}