{"id":"W2951337953","doi":"10.1142/9789811203527_0010","title":"An Ensemble of Character Features and Fine-Tuned Convolutional Neural Network for Spurious Coin Detection","year":2019,"lang":"en","type":"book-chapter","venue":"WORLD SCIENTIFIC eBooks","topic":"Currency Recognition and Detection","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Spurious relationship; Convolutional neural network; Character (mathematics); Computer science; Pattern recognition (psychology); Artificial intelligence; Machine learning; Mathematics","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":[0.0007524416,0.001087965,0.001585999,0.001376559,0.0005038466,0.0007973474,0.001573796,0.001146976,0.002397301],"category_scores_gemma":[0.0009061054,0.0004586724,0.0008735812,0.001144577,0.0002833245,0.001520165,0.001171872,0.00101744,0.001761037],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006052015,"about_ca_system_score_gemma":0.0009646082,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009002769,"about_ca_topic_score_gemma":0.01771923,"domain_scores_codex":[0.9995517,0.0000476855,0.00002137614,0.0001418943,0.0001305035,0.0001068768],"domain_scores_gemma":[0.9995729,0.00007676176,0.00002846856,0.00007748076,0.0002006236,0.00004363537],"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":[0.0004549403,0.0002558726,0.00305024,0.00007831006,0.0002285812,0.0001879114,0.00003371898,0.04803326,0.03349011,0.001399682,0.01040836,0.902379],"study_design_scores_gemma":[0.00001023976,0.00007202265,0.001643621,0.00001022898,0.00008641901,0.0001216955,0.00001315157,0.983112,0.0120263,0.0008393367,0.002044509,0.00002040688],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1172257,0.003833083,0.8629144,0.0003326451,0.0006892771,0.0001366843,0.0006318681,0.007270764,0.006965537],"genre_scores_gemma":[0.658756,0.001314151,0.3109093,0.0004502603,0.0003419293,0.0001075868,0.003108035,0.000386191,0.02462664],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009002769,"threshold_uncertainty_score":0.01790076,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0240548891383303,"score_gpt":0.2396285380682081,"score_spread":0.2155736489298778,"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."}}