{"id":"W2807423832","doi":"10.25300/misq/2018/13157","title":"E-Mail Interruptions and Individual Performance: Is There a Silver Lining?1","year":2018,"lang":"en","type":"article","venue":"MIS Quarterly","topic":"Personal Information Management and User Behavior","field":"Decision Sciences","cited_by":137,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Queen's University","funders":"","keywords":"Computer science; Work (physics); Psychology; Internet privacy; Engineering","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":[0.01445846,0.0005595936,0.001112452,0.001464866,0.0005077617,0.002493179,0.001180729,0.001544105,0.002749436],"category_scores_gemma":[0.05025395,0.000444385,0.002088723,0.002250882,0.001283993,0.001595249,0.001319585,0.001466408,0.0003092445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007675945,"about_ca_system_score_gemma":0.0007277046,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003560536,"about_ca_topic_score_gemma":0.002401628,"domain_scores_codex":[0.9895691,0.006845265,0.0008886284,0.001240966,0.001167795,0.0002882597],"domain_scores_gemma":[0.8964937,0.07839806,0.01672668,0.003495375,0.003555706,0.001330432],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001704371,0.0004876068,0.8639484,0.006299372,0.010545,0.0001150532,0.003067684,0.0004251276,0.0002184633,0.001165998,0.001922632,0.1101003],"study_design_scores_gemma":[0.00006709018,0.0009576991,0.9860501,0.002686867,0.004298891,0.0001165522,0.001209873,0.0003403905,0.0002109727,0.001249424,0.002763758,0.00004847685],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7578741,0.226869,0.002808953,0.004212323,0.0006753845,0.0001205373,0.0008944623,0.00005659409,0.006488646],"genre_scores_gemma":[0.9772465,0.01866973,0.001237045,0.0008379147,0.0007077928,0.0001166532,0.0003963965,0.00001717541,0.0007707312],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01445846,"threshold_uncertainty_score":0.07646459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2549806676656497,"score_gpt":0.4186237159090732,"score_spread":0.1636430482434235,"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."}}