{"id":"W4392790005","doi":"10.5539/ass.v20n1p76","title":"Reviewer Acknowledgements for Asian Social Science, Vol. 20, No. 1","year":2024,"lang":"en","type":"article","venue":"Asian Social Science","topic":"Regional Development and Environment","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sociology; Psychology; Regional science; Social science; Data science; Political science; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04329667,0.003346551,0.007322542,0.008510039,0.005715102,0.008615434,0.006072388,0.01487218,0.09778271],"category_scores_gemma":[0.4369487,0.001789993,0.004052983,0.004445445,0.003291249,0.007073317,0.004234815,0.01196607,0.05205277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005518988,"about_ca_system_score_gemma":0.01293992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006863969,"about_ca_topic_score_gemma":0.01042117,"domain_scores_codex":[0.9598555,0.008289323,0.009174043,0.002711537,0.01840126,0.001568321],"domain_scores_gemma":[0.2736548,0.02821301,0.01330144,0.005454035,0.6709706,0.008406177],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002377704,0.000002603481,0.0000510983,0.0004323167,0.000006983607,0.00004065897,0.0000452841,0.000006426077,0.00002370073,0.00009327448,0.9963527,0.002921175],"study_design_scores_gemma":[0.0002401546,0.00003606197,0.0009116987,0.004086257,0.0001038426,0.0006747652,0.0005892427,0.0003134327,0.0002707082,0.001494722,0.9911349,0.0001441945],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.0001297185,0.002473244,0.0008724765,0.1847265,0.8064985,0.000948914,0.0009266402,0.0004474741,0.002976532],"genre_scores_gemma":[0.005115052,0.008016392,0.003516438,0.2207035,0.6789932,0.006459618,0.001897214,0.001263328,0.07403522],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.09778271,"threshold_uncertainty_score":0.3271157,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02715324723908412,"score_gpt":0.3263578012804651,"score_spread":0.299204554041381,"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."}}