{"id":"W4313322257","doi":"10.7287/peerj.14487v0.2/reviews/5","title":"Peer Review #5 of \"An artificial neural network classification method employing longitudinally monitored immune biomarkers to predict the clinical outcome of critically ill COVID-19 patients (v0.2)\"","year":2022,"lang":"en","type":"peer-review","venue":"","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Dalhousie University; Case Western Reserve University","keywords":"Critically ill; Coronavirus disease 2019 (COVID-19); Artificial neural network; Outcome (game theory); Artificial intelligence; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Computer science; Medicine; Intensive care medicine; Mathematics; Internal medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00636297,0.0007545071,0.001094091,0.003887363,0.002577804,0.004862982,0.002390466,0.002058868,0.2028924],"category_scores_gemma":[0.05511591,0.000482644,0.001075131,0.002082472,0.0008280172,0.002464899,0.003001302,0.001573596,0.09583668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001505901,"about_ca_system_score_gemma":0.008272341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007155549,"about_ca_topic_score_gemma":0.01650296,"domain_scores_codex":[0.995079,0.001016649,0.0004468753,0.0004908449,0.002618504,0.0003480753],"domain_scores_gemma":[0.9521738,0.004330364,0.001625037,0.002344795,0.03699078,0.002535254],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000781873,0.00003485256,0.001621826,0.000633325,0.00003808811,0.0002123748,0.00008450508,0.0002778269,0.0007504012,0.001345762,0.8680875,0.1268354],"study_design_scores_gemma":[0.00004817909,0.0000832483,0.004949203,0.000703753,0.00006162364,0.0002468253,0.000296661,0.003374791,0.001489545,0.002735562,0.9859554,0.00005531324],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.0305439,0.02424939,0.07444279,0.1335134,0.3867546,0.008383773,0.02234826,0.009271156,0.3104928],"genre_scores_gemma":[0.1129425,0.01894639,0.04395045,0.01059683,0.05552984,0.002726567,0.02860873,0.004098795,0.7225999],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.993637,"threshold_uncertainty_score":0.6787428,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2456171551484035,"score_gpt":0.509303875055904,"score_spread":0.2636867199075005,"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."}}