{"id":"W4415292521","doi":"10.2749/ghent.2025.0409","title":"Rehabilitation of Structures in India and Lessons Learnt","year":2025,"lang":"","type":"article","venue":"Report","topic":"Structural Engineering and Vibration Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Precast Prestressed Concrete Institute","funders":"","keywords":"Rehabilitation; Work (physics); Government (linguistics); Key (lock)","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002123539,0.0001373585,0.0003115978,0.0004461799,0.00002396229,0.00001938036,0.00004914539,0.0001253214,0.00004755222],"category_scores_gemma":[0.0004055915,0.0001446433,0.00006971302,0.0006358866,0.00006290397,0.00007727355,0.00002611206,0.0001768792,4.596811e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007511998,"about_ca_system_score_gemma":0.00005572366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001624371,"about_ca_topic_score_gemma":0.00002052743,"domain_scores_codex":[0.9989018,0.00002428867,0.0006066254,0.0002131361,0.0001223752,0.0001317135],"domain_scores_gemma":[0.9994503,0.000128017,0.00009060701,0.0002439133,0.00005107782,0.00003607424],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00002589121,0.00002837074,0.1029681,0.002005456,0.0004389973,0.0001044951,0.002386511,0.710479,0.01313968,0.06341527,0.0002689584,0.1047393],"study_design_scores_gemma":[0.0002396927,0.00002206684,0.9328472,0.0001678908,0.00006892227,0.0000267599,0.0005167889,0.05919083,0.003363657,0.002729591,0.0006797666,0.0001468458],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9786397,0.001581728,0.01451258,0.0004583069,0.0004187408,0.0001521886,0.000005042094,0.00005297337,0.004178725],"genre_scores_gemma":[0.9975479,0.0001224095,0.001986695,0.000006415142,0.00001476379,0.000004966243,0.000009011402,0.000009952637,0.0002979058],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8298791,"threshold_uncertainty_score":0.5898381,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005825801767464964,"score_gpt":0.2667894801598646,"score_spread":0.2609636783923996,"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."}}