{"id":"W4411835871","doi":"10.11113/oiji2025.13n1.329","title":"MODORO - Pomodoro App with AI/ML for Enhanced Productivity","year":2025,"lang":"en","type":"article","venue":"Open International Journal of Informatics","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Universiti Teknologi Malaysia","keywords":"Productivity; Computer science; Artificial intelligence; Economics; Macroeconomics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006240945,0.001123415,0.0004303675,0.0006425829,0.0004191949,0.001475413,0.001357641,0.0009062285,0.04691599],"category_scores_gemma":[0.003031704,0.0002957157,0.0006666788,0.0002252795,0.0003052511,0.001689907,0.002999089,0.0008111947,0.01149712],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001656812,"about_ca_system_score_gemma":0.0003338897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003000952,"about_ca_topic_score_gemma":0.0005895059,"domain_scores_codex":[0.9995847,0.00008007658,0.00002734166,0.00007701191,0.0001647067,0.00006625957],"domain_scores_gemma":[0.9992693,0.0003939174,0.00004890541,0.00005883718,0.0001018445,0.0001270892],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002522144,0.001357366,0.004177665,0.002675452,0.0001035126,0.001315921,0.002534199,0.001567322,0.04482719,0.008237435,0.131846,0.7988358],"study_design_scores_gemma":[0.001083112,0.002826842,0.02375805,0.001993847,0.0003932863,0.004433358,0.002105256,0.04631592,0.04195932,0.03566354,0.8389434,0.000524178],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.1442964,0.003872008,0.5770442,0.004020297,0.001985391,0.003588321,0.006495032,0.06839164,0.1903067],"genre_scores_gemma":[0.4650435,0.002888341,0.3730346,0.004166416,0.0008666283,0.004550308,0.003661092,0.004084066,0.141705],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.04691599,"threshold_uncertainty_score":0.1569496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007427101575549331,"score_gpt":0.2773031861873625,"score_spread":0.2698760846118132,"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."}}