{"id":"W4400170167","doi":"10.23977/acss.2024.080407","title":"A Novel Search Algorithm for Enhancing Retrieval Efficiency in Large-Scale Datasets","year":2024,"lang":"en","type":"article","venue":"Advances in Computer Signals and Systems","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Scale (ratio); Data mining; Information retrieval; Algorithm; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00187281,0.000765726,0.001746987,0.002603294,0.0008778734,0.001292765,0.001853287,0.001774587,0.002246035],"category_scores_gemma":[0.007475127,0.0003853659,0.000793162,0.003872331,0.0005283663,0.003096685,0.001182037,0.00107278,0.00150411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006433176,"about_ca_system_score_gemma":0.001556626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002942926,"about_ca_topic_score_gemma":0.003611571,"domain_scores_codex":[0.9985864,0.0002861441,0.0001595252,0.0002736704,0.0005955088,0.00009874287],"domain_scores_gemma":[0.9972982,0.00120521,0.0001906608,0.0003525607,0.0008556088,0.00009771144],"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":[0.0004537889,0.0003524438,0.002590719,0.0003209109,0.0002052347,0.0001437673,0.0001382589,0.1115765,0.02483081,0.01437259,0.01691224,0.8281026],"study_design_scores_gemma":[0.0001234288,0.0001559714,0.0006539019,0.00001887282,0.0000457989,0.0003212664,0.0000345523,0.9807936,0.005868376,0.00676773,0.005186163,0.00003036149],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01170478,0.0008719633,0.9850213,0.0001775896,0.000120744,0.0001069226,0.0001119788,0.0009110838,0.0009735044],"genre_scores_gemma":[0.1311306,0.000549836,0.8637441,0.000307417,0.0002257985,0.0003006178,0.0007302388,0.0001765755,0.002834779],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002942926,"threshold_uncertainty_score":0.009904444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02359759681104664,"score_gpt":0.3156612217097522,"score_spread":0.2920636248987056,"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."}}