{"id":"W2983041270","doi":"10.18280/ts.360402","title":"Generating Random Numbers from Biological Signals in LabVIEW Environment and Statistical Analysis","year":2019,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Statistical analysis; Statistics; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002657326,0.0001222816,0.0002622014,0.00005251209,0.00005502035,0.00009190854,0.0002277428,0.00003833998,0.0009646516],"category_scores_gemma":[0.00000309811,0.00009651871,0.00005449041,0.0002363836,0.00003566812,0.00009953525,0.0001068422,0.00009209904,0.00005116168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002219906,"about_ca_system_score_gemma":0.000008101398,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007432878,"about_ca_topic_score_gemma":0.00001524508,"domain_scores_codex":[0.9987583,0.0001223204,0.000300456,0.0004321315,0.0001785091,0.0002082802],"domain_scores_gemma":[0.9993463,0.0003156054,0.00006407058,0.0001814517,0.000006675809,0.00008595431],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001307056,0.0008979355,0.3925148,0.00003047708,0.0008835432,0.00008076265,0.001258618,0.2785616,0.07475547,0.05576752,0.001145983,0.1939726],"study_design_scores_gemma":[0.001621656,0.0001089828,0.07838915,0.00001396667,0.00006893044,0.000001420515,0.00002923523,0.9153392,0.0003045394,0.002061467,0.001774633,0.0002868339],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5665362,0.0001543466,0.4327139,0.0002777492,0.00001440267,0.0002065552,0.00001742913,0.0000187016,0.00006068134],"genre_scores_gemma":[0.9733203,0.00009088426,0.02601652,0.0004265791,0.00004271289,0.00004408013,0.00003845718,0.000003490071,0.00001699916],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6367776,"threshold_uncertainty_score":0.9999486,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01750220091416922,"score_gpt":0.2360066360652788,"score_spread":0.2185044351511096,"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."}}