{"id":"W3209533960","doi":"10.1002/ima.22666","title":"Whole slide cervical image classification based on convolutional neural network and random forest","year":2021,"lang":"en","type":"article","venue":"International Journal of Imaging Systems and Technology","topic":"AI in cancer detection","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Aging","funders":"National Natural Science Foundation of China","keywords":"Random forest; Convolutional neural network; Computer science; Artificial intelligence; Pattern recognition (psychology); Feature extraction; Principal component analysis; Feature (linguistics); Classifier (UML)","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":[0.0006274963,0.001027804,0.0007146329,0.001728628,0.0002765112,0.0004135947,0.0007139117,0.0005912461,0.000983099],"category_scores_gemma":[0.001142938,0.0002285607,0.0009107952,0.0008431571,0.0001822649,0.0007642006,0.0003610615,0.0004361545,0.0003937386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006236813,"about_ca_system_score_gemma":0.000589329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0120764,"about_ca_topic_score_gemma":0.01130596,"domain_scores_codex":[0.9995089,0.00004471277,0.00002648298,0.0001538109,0.000163965,0.0001021764],"domain_scores_gemma":[0.9996237,0.00008851833,0.00005049551,0.00005260026,0.0001571778,0.00002755482],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007826553,0.0003525444,0.02716045,0.0001684496,0.0002954431,0.0003938042,0.00006659342,0.1397866,0.04803263,0.0008942185,0.006744645,0.7753219],"study_design_scores_gemma":[0.000009727401,0.0001111325,0.006799621,0.000009666624,0.0000533117,0.0001041653,0.00002024084,0.9817079,0.01033924,0.0003048787,0.0005260838,0.00001397938],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5773165,0.002726348,0.4083697,0.0004594622,0.0002894938,0.0003281762,0.001540219,0.004950882,0.004019141],"genre_scores_gemma":[0.9213087,0.0004385168,0.07298173,0.00008328474,0.00005575371,0.00008589677,0.002478168,0.00004754291,0.002520323],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0120764,"threshold_uncertainty_score":0.02401221,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009071956171855461,"score_gpt":0.2482158553917342,"score_spread":0.2391438992198787,"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."}}