{"id":"W1675192307","doi":"10.1063/1.3026417","title":"A Statistical Model for Scalar Collision-Sequence Interference","year":2008,"lang":"en","type":"article","venue":"AIP conference proceedings","topic":"Embedded Systems Design Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Collision; Computer science; Sequence (biology); Interference (communication); Scalar (mathematics); Statistical model; Algorithm; Artificial intelligence; Computer network; Mathematics; Computer security; Geometry","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005107165,0.0003151078,0.0004060206,0.0001745399,0.0002970193,0.0002969177,0.001908503,0.0001768424,0.00000955522],"category_scores_gemma":[0.0004317623,0.0002954778,0.00007943387,0.0003722034,0.000259391,0.001280988,0.0003574408,0.0002623234,0.00004395206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001300653,"about_ca_system_score_gemma":0.0004731075,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002548744,"about_ca_topic_score_gemma":0.000002899564,"domain_scores_codex":[0.9975023,0.00001869773,0.0005275753,0.0008781932,0.0004711509,0.0006020468],"domain_scores_gemma":[0.9978366,0.000194604,0.0002101881,0.000384725,0.001126694,0.0002472246],"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":[0.0000401068,0.0001058147,0.002716968,0.000144438,0.00001917879,0.0000191209,0.006433575,0.000008339085,0.03565564,0.9352244,0.0161096,0.003522793],"study_design_scores_gemma":[0.00025025,0.0002825552,0.0001454091,0.000137528,0.000006346414,0.0001373647,0.00006031013,0.9182786,0.006637204,0.07340819,0.0002758284,0.0003803777],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0107738,0.00002733126,0.9848476,0.0004956139,0.00009829953,0.0008202681,0.00002647037,0.0007536898,0.002156921],"genre_scores_gemma":[0.6713529,0.00003129531,0.3275108,0.0002472901,0.00003037591,0.0003499467,0.000002846866,0.00001681504,0.000457712],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9182703,"threshold_uncertainty_score":0.9999498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09067455683538253,"score_gpt":0.3072629669852454,"score_spread":0.2165884101498628,"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."}}