{"id":"W3202384358","doi":"10.32920/ryerson.14663658.v1","title":"Convolutional neural network for image classification based on transfer learning technique","year":2021,"lang":"en","type":"preprint","venue":"","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Convolutional neural network; Computer science; Artificial intelligence; Transfer of learning; Artificial neural network; Deep learning; Contextual image classification; Machine learning; MATLAB; Interface (matter); Network architecture; Pattern recognition (psychology); Time delay neural network; Image (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":[0.0006188679,0.0006990363,0.0005415812,0.0009381459,0.0002871565,0.0008053631,0.001072448,0.0008987089,0.00478728],"category_scores_gemma":[0.001562509,0.000273823,0.0007879016,0.001270254,0.0006342134,0.001376019,0.0009126829,0.001870368,0.002795428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009908652,"about_ca_system_score_gemma":0.0007644122,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003401885,"about_ca_topic_score_gemma":0.002669004,"domain_scores_codex":[0.9996431,0.00004905064,0.00002323504,0.00008406622,0.000161541,0.00003896188],"domain_scores_gemma":[0.9996747,0.0001070718,0.00003332256,0.00006661745,0.0001011147,0.00001725813],"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":[0.0001411847,0.0001060821,0.0008250109,0.0004090951,0.0001446144,0.0002349436,0.0001043643,0.2362479,0.03986339,0.0890655,0.0134798,0.6193782],"study_design_scores_gemma":[0.000006046985,0.00003459961,0.0004085767,0.00002820146,0.00001826401,0.0001231195,0.000008147831,0.9555457,0.01212727,0.02094019,0.01074406,0.00001575118],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003661701,0.001018528,0.9889919,0.0002333831,0.0001217746,0.00005743716,0.0001110661,0.001484199,0.004320068],"genre_scores_gemma":[0.2554851,0.002691923,0.7215424,0.0002936464,0.0002457914,0.0002930705,0.0007810527,0.0004558811,0.01821131],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00478728,"threshold_uncertainty_score":0.01601499,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05546515822773012,"score_gpt":0.3394901634711576,"score_spread":0.2840250052434275,"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."}}