{"id":"W6891807969","doi":"10.48448/rw68-tz57","title":"A Study on the Efficiency and Generalization of Light Hybrid Retrievers","year":2022,"lang":"en","type":"other","venue":"Underline Science Inc.","topic":"Smart Grid Security and Resilience","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Leverage (statistics); Generalization; Robustness (evolution); Hybrid system; Set (abstract data type); Labrador Retriever","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005965597,0.002141067,0.002137318,0.002079663,0.0009025515,0.002099684,0.003304668,0.002064647,0.003645225],"category_scores_gemma":[0.01789983,0.0005784935,0.001403062,0.001942505,0.001366434,0.006512712,0.00203507,0.001909071,0.003089241],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001127271,"about_ca_system_score_gemma":0.0009849961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004846806,"about_ca_topic_score_gemma":0.004784806,"domain_scores_codex":[0.9965529,0.0007572403,0.0003651909,0.0007955951,0.00115767,0.0003713701],"domain_scores_gemma":[0.9895523,0.004254191,0.0007855025,0.004013475,0.001135029,0.0002594141],"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":[0.001934854,0.001045811,0.01225479,0.0007927986,0.0009042633,0.0005402765,0.0004319237,0.2478709,0.0445466,0.006925753,0.02095891,0.6617932],"study_design_scores_gemma":[0.000169878,0.0008686046,0.003617537,0.00005832506,0.0002033771,0.000723486,0.0002419686,0.9562643,0.026352,0.005953512,0.005463706,0.00008325584],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5725377,0.01594668,0.3730128,0.002625987,0.0004208505,0.0005159481,0.001946576,0.01963174,0.01336176],"genre_scores_gemma":[0.842913,0.002099431,0.1395589,0.00129664,0.0004123382,0.0002421795,0.003572329,0.001169326,0.008735809],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005965597,"threshold_uncertainty_score":0.03154945,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01213230905976866,"score_gpt":0.2312450997842239,"score_spread":0.2191127907244553,"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."}}