{"id":"W4379522696","doi":"10.21428/594757db.8bee12fd","title":"Parameter-Efficient Methods for Metastases Detection fromClinical Notes","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Vector Institute","keywords":"Leverage (statistics); Computer science; Transfer of learning; Domain adaptation; Artificial intelligence; F1 score; Task (project management); Machine learning; Recall; Adaptation (eye)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00313077,0.002379782,0.001186029,0.002947994,0.0006393986,0.001297996,0.003763136,0.002376805,0.003433596],"category_scores_gemma":[0.01090842,0.0008027878,0.001659474,0.001873655,0.0008591421,0.002433467,0.002496144,0.002673812,0.00493814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00120151,"about_ca_system_score_gemma":0.001777868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005870276,"about_ca_topic_score_gemma":0.008309445,"domain_scores_codex":[0.9977382,0.0007073788,0.0001957562,0.000761166,0.0004482555,0.0001491047],"domain_scores_gemma":[0.9955022,0.00208797,0.0004449972,0.001168085,0.0006874632,0.0001092972],"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":[0.0002514741,0.0002024625,0.002230885,0.0003027579,0.0001601827,0.0002567244,0.0001469215,0.1188483,0.0185262,0.00357381,0.01329428,0.8422059],"study_design_scores_gemma":[0.00003789341,0.00006035304,0.001074692,0.00002873049,0.00003378613,0.0002173498,0.00005519973,0.9721711,0.01136658,0.009325496,0.005590505,0.0000383736],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009310488,0.0009267704,0.9763946,0.0003039921,0.000088884,0.000153544,0.0006741151,0.01140632,0.0007411936],"genre_scores_gemma":[0.2089055,0.0009572963,0.7721429,0.0004045301,0.0003263018,0.0007678019,0.007160419,0.001487928,0.007847295],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005870276,"threshold_uncertainty_score":0.01655728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1136882294077211,"score_gpt":0.4784114546064754,"score_spread":0.3647232251987543,"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."}}