{"id":"W4414681735","doi":"10.1007/978-3-032-02725-2_10","title":"Advancing Imminent Fracture Risk Prediction: Integrating Machine Learning with Enhanced Feature Engineering","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Topic Modeling","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Lift (data mining); Feature engineering; Upsampling; Risk assessment; Ensemble learning; Deep learning; Missing data","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":[0.0009030333,0.0007568146,0.001117172,0.00101399,0.0002351804,0.001372162,0.001268179,0.0008240945,0.002554997],"category_scores_gemma":[0.004145149,0.0003100295,0.0008126194,0.0008755753,0.0002199953,0.001672758,0.00101371,0.001147047,0.001214685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002830394,"about_ca_system_score_gemma":0.000470461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002734239,"about_ca_topic_score_gemma":0.003083137,"domain_scores_codex":[0.9996989,0.00005704271,0.00001623429,0.00007883689,0.0001211209,0.00002803878],"domain_scores_gemma":[0.9987098,0.0007498113,0.0001132554,0.0001219623,0.0002625584,0.00004265165],"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":[0.00009923225,0.0001801809,0.005625877,0.0001248439,0.00009559649,0.00008216668,0.00003681544,0.1977627,0.005002492,0.00419232,0.007800447,0.7789974],"study_design_scores_gemma":[0.000005008205,0.00004155305,0.001000381,0.00001317282,0.0000207256,0.00004689572,0.000009839893,0.9875794,0.001409276,0.008471585,0.001392449,0.000009683645],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0322851,0.002023337,0.958091,0.0006328474,0.0001851374,0.00003395216,0.0003352,0.001865906,0.004547446],"genre_scores_gemma":[0.5862249,0.001831537,0.4051163,0.0002324466,0.0005422016,0.00006118469,0.001044397,0.0002956257,0.004651512],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002734239,"threshold_uncertainty_score":0.008547246,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003651834518784236,"score_gpt":0.2012329747891235,"score_spread":0.1975811402703392,"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."}}