{"id":"W2092935629","doi":"10.1080/10637199808947384","title":"RANDOMIZED OPTIMAL LIST RANKING ON COARSE-GRAINED PARALLEL COMPUTERS WITH O(log p) COMMUNICATION PHASES","year":2000,"lang":"en","type":"article","venue":"International Journal of Parallel Emergent and Distributed Systems","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Computer science; Ranking (information retrieval); Computation; Parallel algorithm; Cost efficiency; Parallel computing; Randomized algorithm; Theoretical computer science; Algorithm; Information retrieval","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001207,0.0002669474,0.0006059601,0.0002477624,0.000215637,0.0004302044,0.001270066,0.00008193836,0.00005142658],"category_scores_gemma":[0.00009092432,0.0002007612,0.0001995689,0.0002171459,0.0001408912,0.0004608344,0.00009442918,0.000278155,0.000005553706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008135348,"about_ca_system_score_gemma":0.00007179468,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008590682,"about_ca_topic_score_gemma":0.000003087446,"domain_scores_codex":[0.9971645,0.0005316203,0.001018441,0.0002751876,0.0007725796,0.0002376719],"domain_scores_gemma":[0.9976591,0.0004173642,0.000776706,0.0003250126,0.0006565595,0.0001652842],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.01326015,0.000337368,0.0002411457,0.00001345451,0.0006601302,0.00009732426,0.0006847996,0.9482094,0.00001741527,0.0198111,0.01251975,0.00414796],"study_design_scores_gemma":[0.05585954,0.0003509813,0.00008699256,0.0004792281,0.00005489156,0.000428852,0.0001012186,0.9284383,0.00002913572,0.0005285919,0.0132575,0.0003847377],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01913208,0.001048227,0.9761373,0.001839039,0.0005505756,0.0003318774,0.00002165812,0.0001257479,0.0008134805],"genre_scores_gemma":[0.9362836,0.001268405,0.06169358,0.0002008605,0.0001801724,0.00002148294,0.000108973,0.00001365588,0.0002292851],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9171515,"threshold_uncertainty_score":0.8186804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01786713948870236,"score_gpt":0.275782526090011,"score_spread":0.2579153866013086,"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."}}