{"id":"W4395662003","doi":"10.1109/lascas60203.2024.10506129","title":"Light Siamese Neural Network Architecture for Image Comparison","year":2024,"lang":"en","type":"article","venue":"","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Computer science; Convolutional neural network; Artificial neural network; Artificial intelligence; Perceptron; Pattern recognition (psychology); Similarity (geometry); Deep learning; Image processing; Cellular neural network; Image (mathematics); Machine learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001133901,0.0008344006,0.0006074006,0.001300971,0.0003966873,0.00133068,0.001610817,0.001022735,0.02074848],"category_scores_gemma":[0.003082333,0.0002741625,0.0005608569,0.001393945,0.0004920982,0.001966954,0.001338904,0.001284668,0.004787318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000972349,"about_ca_system_score_gemma":0.001201266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006385799,"about_ca_topic_score_gemma":0.008346649,"domain_scores_codex":[0.9993429,0.00009644649,0.00004099389,0.0002074113,0.0002478941,0.00006432274],"domain_scores_gemma":[0.999315,0.00009181271,0.0000427091,0.000163718,0.0003433817,0.00004330325],"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":[0.0003533463,0.0001467981,0.00100232,0.0002008941,0.0001351202,0.0001110746,0.00005288967,0.1190057,0.0337115,0.04172112,0.03181934,0.77174],"study_design_scores_gemma":[0.00001787801,0.00007200695,0.0005968222,0.00001794183,0.00001258883,0.0001148384,0.00001633462,0.9548502,0.01374325,0.01607291,0.01446009,0.0000251459],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01301076,0.001089921,0.967047,0.0005039417,0.0002866689,0.0001804751,0.0006972937,0.005241749,0.01194206],"genre_scores_gemma":[0.2814098,0.0009828518,0.6861436,0.0006093134,0.0001872694,0.0004527008,0.003160807,0.0008905153,0.02616321],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02074848,"threshold_uncertainty_score":0.06941056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01168038505579909,"score_gpt":0.300426899503841,"score_spread":0.2887465144480419,"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."}}