{"id":"W2883417695","doi":"10.1373/jalm.2017.025817","title":"Algorithms Used in Ovarian Cancer Detection: A Minireview on Current and Future Applications","year":2018,"lang":"en","type":"article","venue":"The Journal of Applied Laboratory Medicine","topic":"Ovarian cancer diagnosis and treatment","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University Health Network; University of Toronto","funders":"","keywords":"Ovarian cancer; Serous fluid; Malignancy; Disease; Medicine; Cancer; Oncology; Algorithm; Stage (stratigraphy); Internal medicine; Asymptomatic; Gynecology; Biology; Computer science","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":[0.006269659,0.00122923,0.00196954,0.005224528,0.0004401718,0.002228874,0.002349682,0.001980363,0.004260032],"category_scores_gemma":[0.02202392,0.0006648115,0.00199578,0.003466817,0.001149721,0.003382571,0.001209696,0.002841919,0.003094656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00151531,"about_ca_system_score_gemma":0.002531466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002416973,"about_ca_topic_score_gemma":0.002532334,"domain_scores_codex":[0.9969938,0.0008812491,0.0006428924,0.0003547651,0.001014195,0.0001131989],"domain_scores_gemma":[0.9854488,0.008901118,0.0009522768,0.0003530219,0.004077326,0.0002675704],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007462015,0.0000442289,0.001204893,0.01439153,0.0001472109,0.0001112898,0.0001362884,0.00057523,0.0004531247,0.001982967,0.04382814,0.9370505],"study_design_scores_gemma":[0.00003938745,0.000255851,0.004409421,0.03138874,0.0006537774,0.002604412,0.0002949442,0.001479408,0.001181572,0.007901157,0.9496639,0.0001275556],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003032363,0.9893565,0.003194624,0.003391157,0.002193452,0.0000682966,0.00007499978,0.000106423,0.001311404],"genre_scores_gemma":[0.00187944,0.9867621,0.006368712,0.001681769,0.002343929,0.00009109439,0.0001518164,0.00004452947,0.0006766127],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.006269659,"threshold_uncertainty_score":0.03315753,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02273378916698138,"score_gpt":0.3249751197026542,"score_spread":0.3022413305356728,"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."}}