{"id":"W2048014304","doi":"10.4236/ojrm.2013.22004","title":"Clinical translation of neuro-regenerative medicine in India: A study on barriers and enabling strategies","year":2013,"lang":"en","type":"article","venue":"Open Journal of Regenerative Medicine","topic":"Biotechnology and Related Fields","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University Health Network","funders":"Canadian Institutes of Health Research","keywords":"Standardization; Government (linguistics); Multidisciplinary approach; Clinical trial; Protocol (science); Translational medicine; Regenerative medicine; Medicine; Alternative medicine; Engineering ethics; Psychology; Business; Political science; Engineering; Pathology","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":[0.1097574,0.0005541555,0.0009982018,0.003007561,0.01721097,0.01817096,0.004197234,0.003730793,0.004681105],"category_scores_gemma":[0.173588,0.001454109,0.0007987691,0.005623256,0.01953603,0.00775706,0.0192277,0.007607083,0.0005806888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01645531,"about_ca_system_score_gemma":0.0736176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02006385,"about_ca_topic_score_gemma":0.01370507,"domain_scores_codex":[0.8304986,0.1215493,0.01315433,0.003990757,0.01580497,0.01500209],"domain_scores_gemma":[0.6572527,0.2725924,0.03140938,0.009007937,0.01627095,0.01346667],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001111564,0.0001629503,0.02542398,0.001480311,0.00004151709,0.002094377,0.9271005,0.0001224994,0.0008551375,0.01649214,0.001488421,0.02462702],"study_design_scores_gemma":[0.00003121441,0.0001436746,0.01040083,0.00131105,0.00003912328,0.0007292012,0.9637632,0.0002195091,0.000527915,0.003399263,0.01937252,0.00006239005],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9107841,0.003050345,0.004249923,0.05987816,0.0002231454,0.001243787,0.0001475137,0.00007654736,0.02034639],"genre_scores_gemma":[0.9928933,0.0009382574,0.001524605,0.003530697,0.00002253798,0.0003971913,0.0000233524,0.00002522753,0.0006448202],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1097574,"threshold_uncertainty_score":0.5804597,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05782589866908878,"score_gpt":0.3840849811823745,"score_spread":0.3262590825132857,"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."}}