{"id":"W1545895816","doi":"10.1007/978-3-642-15274-0_12","title":"Series Transformations to Improve and Extend Convergence","year":2010,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Sports Dynamics and Biomechanics","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Convergence (economics); Transformation (genetics); Computer science; Series (stratigraphy); Invariant (physics); Maple; Applied mathematics; Domain (mathematical analysis); Function (biology); Algorithm; Algebra over a field; Mathematics; Pure mathematics; Mathematical analysis","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":[0.001603397,0.001369891,0.0008867088,0.001700423,0.0006562387,0.001038286,0.0009992132,0.0007130678,0.0125255],"category_scores_gemma":[0.008137764,0.000364144,0.001461967,0.001425929,0.001812501,0.003430238,0.002873557,0.002746094,0.003716555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004594973,"about_ca_system_score_gemma":0.0004062114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003294371,"about_ca_topic_score_gemma":0.0003418332,"domain_scores_codex":[0.9991404,0.000299072,0.00007221038,0.0001615898,0.0002500144,0.0000767751],"domain_scores_gemma":[0.9979849,0.0009351218,0.00009965619,0.0004933449,0.0003700195,0.0001169278],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002250348,0.0001623555,0.0003159523,0.0002195516,0.00005412988,0.0001583005,0.0004475289,0.02452126,0.0169251,0.654139,0.008585481,0.2942464],"study_design_scores_gemma":[0.00009633102,0.000409805,0.0003395605,0.00007979004,0.00009387274,0.0004501145,0.0001561476,0.1800518,0.02687941,0.7443445,0.04705017,0.00004849781],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02188929,0.0007630119,0.9446869,0.0003131454,0.0006436593,0.00004784084,0.00006706912,0.001407619,0.03018146],"genre_scores_gemma":[0.4855891,0.00316941,0.42033,0.0007661674,0.001445284,0.0002528415,0.000490011,0.004432127,0.08352497],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0125255,"threshold_uncertainty_score":0.04190195,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004523693658604937,"score_gpt":0.190044449845278,"score_spread":0.1855207561866731,"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."}}