{"id":"W4402401640","doi":"10.1109/tvcg.2024.3456163","title":"A Framework for Multimodal Medical Image Interaction","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Visualization; Human–computer interaction; Computer vision; Image (mathematics); Computer graphics (images); Artificial intelligence","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":[0.0002467619,0.0001538742,0.0001279974,0.0003418836,0.0002112605,0.0004696239,0.0002465954,0.0001751014,0.00002674831],"category_scores_gemma":[0.000007837329,0.0001410756,0.0001181431,0.0006628699,0.00007214268,0.0005489804,0.000004289278,0.0002512309,0.00001287056],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000258062,"about_ca_system_score_gemma":0.00006250323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003949295,"about_ca_topic_score_gemma":0.000001651381,"domain_scores_codex":[0.9987903,0.00006220718,0.000259575,0.0004157823,0.000313373,0.0001588111],"domain_scores_gemma":[0.9991683,0.0003220054,0.00004032102,0.0002163019,0.0001344188,0.0001186935],"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":[0.00001000003,0.0001004202,8.56654e-7,0.0000658634,0.00002574863,0.0000031027,0.0003288524,0.000002955679,0.00003923456,0.9020281,0.0001978853,0.097197],"study_design_scores_gemma":[0.0001490164,0.0001789802,0.00001742246,0.0001623783,0.00001297282,0.00002798357,0.00001268381,0.9716516,0.01123689,0.01171952,0.00466531,0.0001652111],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0001548154,0.00006346897,0.996671,0.0006101057,0.001290254,0.0002560491,0.000008741242,0.0009164165,0.00002918056],"genre_scores_gemma":[0.9179634,0.0007061179,0.07868311,0.002082274,0.0002412897,0.0001677383,0.00001270512,0.00003865216,0.0001047307],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9716487,"threshold_uncertainty_score":0.5752895,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02658585601230873,"score_gpt":0.347016048474245,"score_spread":0.3204301924619363,"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."}}