{"id":"W3209058263","doi":"10.1113/ep089834","title":"Data analysis technique influences blood flow kinetics parameter estimates for moderate‐ and heavy‐intensity exercise transitions","year":2021,"lang":"en","type":"article","venue":"Experimental Physiology","topic":"Cardiovascular and exercise physiology","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto General Hospital; Redeemer University; Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Blood flow; Confidence interval; Cycle ergometer; Doppler ultrasound; Transition time; Hemodynamics; Cardiac cycle; Physical exercise; Doppler effect","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00007266129,0.0002144703,0.0009596599,0.00009476257,0.0001156856,0.00001935817,0.0001141512,0.0001416764,0.00006951833],"category_scores_gemma":[0.00005878909,0.0001935804,0.000325267,0.0002369502,0.0002488845,0.00009386838,0.0001832797,0.0001216538,0.000003348005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000159886,"about_ca_system_score_gemma":0.00003943474,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004318926,"about_ca_topic_score_gemma":0.000008129493,"domain_scores_codex":[0.998646,0.00004482547,0.0002494968,0.0006882332,0.00009235992,0.0002790963],"domain_scores_gemma":[0.9987966,0.00009774553,0.00003939614,0.0008229385,0.0001252267,0.0001180256],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003215618,0.0006326351,0.00002056899,0.00006564989,0.001521425,0.00003084843,0.0002139894,0.0005273862,0.9932424,0.00002951642,0.0002524089,0.0002475553],"study_design_scores_gemma":[0.001178989,0.0003512439,0.007236538,0.00003376976,0.003208163,0.0001756334,0.0003115644,0.01525057,0.9709508,0.001025768,0.00005518868,0.0002217912],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.98577,0.005341752,0.007498774,0.0002194498,0.00009684797,0.0006070498,0.000346866,0.00007379058,0.00004548274],"genre_scores_gemma":[0.9661157,0.0001472014,0.0306404,0.0003498921,0.00008246081,0.0002234676,0.002405969,0.00002022429,0.00001472711],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02314162,"threshold_uncertainty_score":0.789398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03249887306541632,"score_gpt":0.3181793728591051,"score_spread":0.2856804997936888,"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."}}