{"id":"W2033947775","doi":"10.1109/wescan.1993.270572","title":"Garbage collection software integrated with the system swapper in a virtual memory system","year":2002,"lang":"en","type":"article","venue":"","topic":"Handwritten Text Recognition Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Garbage; Garbage collection; Computer science; Lisp; Manual memory management; Modular design; Table (database); Hash table; Operating system; Software; Virtual memory; Database; Memory management; Programming language; Hash function","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":[0.0009567934,0.0006557379,0.000680879,0.001164014,0.0004903157,0.001246266,0.001760645,0.0004129981,0.005916519],"category_scores_gemma":[0.003305877,0.0005908585,0.0003512485,0.0007980916,0.0006852131,0.001747599,0.0009204039,0.0006296416,0.001786565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005949152,"about_ca_system_score_gemma":0.001232281,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001273005,"about_ca_topic_score_gemma":0.0007977609,"domain_scores_codex":[0.9992185,0.0001787454,0.00007979335,0.0001434077,0.000288035,0.00009149827],"domain_scores_gemma":[0.9977174,0.0006197559,0.0001496938,0.0008136326,0.0005933993,0.0001061726],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00274277,0.0003729775,0.007197978,0.000815994,0.0001891983,0.0007482689,0.001955466,0.03765175,0.1828349,0.02361645,0.01262624,0.729248],"study_design_scores_gemma":[0.0002727981,0.001124941,0.003464626,0.0001202334,0.0002372934,0.000858686,0.0002484602,0.1904752,0.7296348,0.006910006,0.06649764,0.0001553878],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1495751,0.0004025262,0.7288312,0.0001007351,0.0001039013,0.0003026011,0.000339968,0.1135013,0.006842791],"genre_scores_gemma":[0.56287,0.0002629362,0.4163363,0.0001531782,0.00003375492,0.0003269541,0.0009743571,0.005159594,0.01388295],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005916519,"threshold_uncertainty_score":0.01979268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01046191183328004,"score_gpt":0.1910487011355642,"score_spread":0.1805867893022842,"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."}}