{"id":"W2096701874","doi":"10.1109/imcsit.2010.5679866","title":"SyMGiza++: A tool for parallel computation of symmetrized word alignment models","year":2010,"lang":"en","type":"article","venue":"Proceedings of the International Multiconference on Computer Science and Information Technology","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computation; Word (group theory); Computer science; IBM; Task (project management); Series (stratigraphy); Simple (philosophy); Parallel computing; Algorithm; Theoretical computer science; Mathematics; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006349378,0.0001181984,0.0001593703,0.0007485966,0.0001312241,0.000226118,0.002321783,0.00009571804,6.075658e-7],"category_scores_gemma":[0.0004421872,0.00008544097,0.00003995404,0.0007327102,0.0004263487,0.003294343,0.0007077453,0.0001850272,7.056471e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004223779,"about_ca_system_score_gemma":0.00012272,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000649904,"about_ca_topic_score_gemma":3.716801e-7,"domain_scores_codex":[0.9985896,0.00000198409,0.0004289178,0.0002187937,0.0005937362,0.0001670033],"domain_scores_gemma":[0.997144,0.00006059983,0.0005235036,0.0001663954,0.002075879,0.00002965616],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001349161,0.00002960324,0.0001101144,0.00002967252,0.000006551673,1.670189e-8,0.0002464455,0.00005745502,0.02184387,0.8249844,0.00005082401,0.1526275],"study_design_scores_gemma":[0.000374226,0.0001024439,0.0001724093,0.00008443562,0.000002763063,0.000009434452,0.00002742681,0.6588295,0.1692841,0.1709033,0.0001144896,0.00009552388],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1421285,0.000009386312,0.852074,0.004451224,0.0004708724,0.0004765129,0.000005392593,0.0001474456,0.0002366126],"genre_scores_gemma":[0.5853947,0.000004962391,0.4143497,0.0002104702,0.000009164002,0.00002687841,5.31442e-7,0.000001542426,0.000002071818],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.658772,"threshold_uncertainty_score":0.4314488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01249131424737963,"score_gpt":0.2589930155183056,"score_spread":0.2465017012709259,"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."}}