{"id":"W4415681780","doi":"10.1007/978-981-95-4142-3_9","title":"BFCSR: A Blockchain-Based Federated Learning Framework with Client Selection and Round-Based Training Scheme","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Bombardier (Canada)","funders":"","keywords":"Federated learning; Scheme (mathematics); Selection (genetic algorithm); Training (meteorology); Training set; Feature selection","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":[0.001683638,0.0005240042,0.001171838,0.000811671,0.001344043,0.001697574,0.002869903,0.001482499,0.01674273],"category_scores_gemma":[0.002685536,0.0004092196,0.0005230338,0.001457541,0.001057428,0.003250419,0.002772108,0.001819333,0.004393621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001168402,"about_ca_system_score_gemma":0.003151343,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004751731,"about_ca_topic_score_gemma":0.005050683,"domain_scores_codex":[0.9988304,0.0002868406,0.00005632363,0.0001853777,0.0004357418,0.0002053115],"domain_scores_gemma":[0.9989552,0.0002684576,0.00005282116,0.0004511737,0.0001698387,0.0001023527],"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":[0.001133898,0.0004412656,0.0006089699,0.0002865253,0.00007051951,0.0002731764,0.0002178583,0.2545293,0.008862531,0.2197118,0.03007015,0.4837939],"study_design_scores_gemma":[0.00009520439,0.00009079721,0.0001134429,0.00002945545,0.00001320605,0.0001474105,0.00002986674,0.8722612,0.005419862,0.1020205,0.01974262,0.0000364478],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009041927,0.0002935258,0.9729897,0.0003015859,0.0001329072,0.0003002924,0.0006518941,0.007244127,0.009044101],"genre_scores_gemma":[0.479438,0.0005599827,0.478942,0.0002491749,0.0001001219,0.0004853825,0.001805149,0.0006043835,0.03781584],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01674273,"threshold_uncertainty_score":0.05601001,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04149762602919337,"score_gpt":0.2917048710542572,"score_spread":0.2502072450250638,"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."}}