{"id":"W1563797521","doi":"10.3233/ica-2005-12201","title":"A multiscale approach to pixel-level image fusion","year":2005,"lang":"en","type":"article","venue":"Integrated Computer-Aided Engineering","topic":"Advanced Image Fusion Techniques","field":"Engineering","cited_by":137,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Pixel; Computer vision; Artificial intelligence; Image fusion; Image (mathematics); Computer science; Fusion; Linguistics; Philosophy","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":[0.0001336119,0.0005132802,0.0004117759,0.0004590955,0.00006308691,0.0001147673,0.0004968112,0.0001707268,0.00004392074],"category_scores_gemma":[0.00004343005,0.0005227672,0.0001201986,0.0007115976,0.00002152252,0.0004523903,0.0001687105,0.0005691598,0.0002123204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000319179,"about_ca_system_score_gemma":0.00001460721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001740328,"about_ca_topic_score_gemma":0.000003911469,"domain_scores_codex":[0.9981301,0.00001670792,0.0005030333,0.0004593824,0.0002547004,0.0006360301],"domain_scores_gemma":[0.9989634,0.00005985319,0.00003315025,0.0005289176,0.0001268824,0.0002877602],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00000637566,0.00006017801,0.000003142815,0.0000575115,0.00002930008,0.000008933476,0.0002570093,0.5406112,0.3333147,0.0001198315,0.005073808,0.120458],"study_design_scores_gemma":[0.0002878986,0.00004615825,0.0001447137,0.0001390745,0.000007965378,0.00004901062,0.00001946715,0.8553023,0.1121388,0.00001686329,0.03129259,0.0005551637],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03317935,0.0001203478,0.9588569,0.00005003282,0.000425935,0.0004399827,0.00002843392,0.004943753,0.001955268],"genre_scores_gemma":[0.2305981,0.00002488523,0.7685265,0.00009673442,0.0003335837,0.0001078345,0.00003585837,0.0001417808,0.000134707],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3146911,"threshold_uncertainty_score":0.9997224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01006101852092631,"score_gpt":0.2098511496341799,"score_spread":0.1997901311132536,"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."}}