{"id":"W2098656920","doi":"10.22456/1982-8918.2450","title":"A MECANOGRAFIA COMO TÉCNICA NÃO-INVASIVA PARA O ESTUDO DA FUNÇÃO MUSCULAR","year":2007,"lang":"pt","type":"article","venue":"Movimento (Porto Alegre)","topic":"Mechanics and Biomechanics Studies","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Skeletal muscle; Muscle contraction; Contraction (grammar); Physical medicine and rehabilitation; Medicine; Neuroscience; Physics; Humanities; Psychology; Internal medicine; Philosophy","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":[0.004429657,0.001376723,0.001680175,0.004550402,0.001384514,0.003838308,0.001482707,0.003358351,0.006550337],"category_scores_gemma":[0.006860993,0.0007847699,0.001811688,0.003292673,0.005109115,0.002980404,0.003446711,0.002776844,0.002928355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001236446,"about_ca_system_score_gemma":0.002355716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002391318,"about_ca_topic_score_gemma":0.002258047,"domain_scores_codex":[0.9968509,0.001078971,0.0002220677,0.0007102195,0.0009367256,0.0002010246],"domain_scores_gemma":[0.9951794,0.002515426,0.0006943785,0.0005330749,0.0007831081,0.0002946603],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006903797,0.000178099,0.0280454,0.007529623,0.0004742544,0.003511388,0.00178007,0.001992293,0.1956329,0.05082704,0.01369704,0.6956416],"study_design_scores_gemma":[0.0003017659,0.002644979,0.07453088,0.009865164,0.001445111,0.06413862,0.002520787,0.01444337,0.1313679,0.06348584,0.6344594,0.0007961254],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05967649,0.3393173,0.5090295,0.0141569,0.00447922,0.001105606,0.001403506,0.002133335,0.0686981],"genre_scores_gemma":[0.4343027,0.1958234,0.3107065,0.00959814,0.003951245,0.002763083,0.001070753,0.0005364555,0.04124775],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006550337,"threshold_uncertainty_score":0.02342653,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03467561947269828,"score_gpt":0.2661935802488122,"score_spread":0.2315179607761139,"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."}}