{"id":"W2764252624","doi":"10.1371/journal.pone.0186007","title":"Active and resting motor threshold are efficiently obtained with adaptive threshold hunting","year":2017,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Transcranial Magnetic Stimulation Studies","field":"Neuroscience","cited_by":112,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Transcranial magnetic stimulation; PEST analysis; Intraclass correlation; Computer science; Statistics; Mathematics; Biology; Stimulation; Neuroscience; Reproducibility","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001619734,0.0005953988,0.0005060553,0.0007670457,0.0001611393,0.0004565169,0.0005510261,0.0006198419,0.001397086],"category_scores_gemma":[0.01000938,0.0003488691,0.0003545852,0.0003936302,0.0007883718,0.0009750698,0.0006479446,0.0005205956,0.0003841719],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001607676,"about_ca_system_score_gemma":0.0002265512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005746958,"about_ca_topic_score_gemma":0.001591277,"domain_scores_codex":[0.9985649,0.0003647255,0.0001240548,0.000413546,0.0004730312,0.00005974046],"domain_scores_gemma":[0.997511,0.001230323,0.0005367081,0.0003368751,0.0003143944,0.00007075192],"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":[0.001717426,0.000127805,0.01493769,0.0005367348,0.0001873907,0.0002108149,0.0005892135,0.002194767,0.7366459,0.0007044357,0.0004002601,0.2417475],"study_design_scores_gemma":[0.0002747619,0.004789208,0.4793641,0.000130967,0.0004337565,0.004881073,0.0004275354,0.05817348,0.4403498,0.006964755,0.003912388,0.0002980272],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6266443,0.001367177,0.3669689,0.0001375293,0.00007438241,0.0002542878,0.0002960522,0.00102704,0.003230278],"genre_scores_gemma":[0.8882132,0.0003272654,0.1101545,0.0001047745,0.00003561619,0.0001740326,0.0001830577,0.0001413901,0.0006662398],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001619734,"threshold_uncertainty_score":0.008566022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1171432175889082,"score_gpt":0.2683409871092409,"score_spread":0.1511977695203327,"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."}}