{"id":"W1960744987","doi":"10.1109/mwscas.1990.140737","title":"A floating point convolution system","year":2002,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"VMEbus; Convolution (computer science); Application-specific integrated circuit; Computer science; Very-large-scale integration; Floating point; Interface (matter); Point (geometry); Computer hardware; Integer (computer science); Parallel computing; Embedded system; Operating system; Artificial intelligence; Data acquisition; Mathematics","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":[0.0001562393,0.00005769875,0.00006762637,0.00005676124,0.0001030037,0.00008563953,0.0002935332,0.00002817241,0.00002309215],"category_scores_gemma":[0.00001674474,0.00005139072,0.00002721042,0.0001950642,0.000008706746,0.00020148,0.00008922641,0.0000442758,0.0001452564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004077062,"about_ca_system_score_gemma":0.000004155545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001737319,"about_ca_topic_score_gemma":3.448556e-7,"domain_scores_codex":[0.9994202,0.00003813065,0.0001380996,0.0001674785,0.000107436,0.0001287161],"domain_scores_gemma":[0.9995928,0.00002541901,0.00004658867,0.0002461913,0.00005127422,0.00003776096],"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":[6.876478e-7,0.0000546124,0.0002366233,0.00003500022,0.00001047413,0.00001172169,0.0008594172,0.006720121,0.0002872323,0.918266,0.04021821,0.03329991],"study_design_scores_gemma":[0.00006897665,0.0000179046,0.0000323134,0.00001724547,6.370039e-7,0.0000199132,0.00001688665,0.9977769,0.0009539772,0.0001856666,0.0008372696,0.00007232824],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0002863472,0.00006257257,0.9167789,0.0003196519,0.00010059,0.00005624383,7.654875e-8,0.0018678,0.08052777],"genre_scores_gemma":[0.6283235,0.000002787434,0.3707669,0.0001255122,0.00002147096,0.000001866701,1.957668e-7,0.000002250671,0.000755539],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9910567,"threshold_uncertainty_score":0.2095653,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02004909686967695,"score_gpt":0.2175971893268964,"score_spread":0.1975480924572194,"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."}}