{"id":"W1499526891","doi":"10.1111/isj.12064","title":"The many faces of information technology interruptions: a taxonomy and preliminary investigation of their performance effects","year":2015,"lang":"en","type":"article","venue":"Information Systems Journal","topic":"Personal Information Management and User Behavior","field":"Decision Sciences","cited_by":109,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Taxonomy (biology); Relevance (law); Computer science; Data science; Knowledge management; Psychology; Political science; Ecology; Biology","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":[0.004523413,0.0003361633,0.0004269889,0.002579081,0.001752405,0.0026732,0.0007301181,0.0007452907,0.002989551],"category_scores_gemma":[0.0326263,0.0002297951,0.0005102304,0.002251456,0.001672883,0.001955833,0.002571926,0.0009232669,0.0002422608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001419847,"about_ca_system_score_gemma":0.0009053167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001828935,"about_ca_topic_score_gemma":0.002404095,"domain_scores_codex":[0.9950539,0.002086292,0.000546478,0.0002178579,0.00163506,0.0004603913],"domain_scores_gemma":[0.9376913,0.04666687,0.00672501,0.001738255,0.005752316,0.001426261],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001038136,0.0006691559,0.558834,0.002028153,0.0001378458,0.000682775,0.141616,0.002081468,0.006528019,0.01201474,0.001625656,0.272744],"study_design_scores_gemma":[0.00003844472,0.001035422,0.8237788,0.0006916131,0.0001531564,0.0006947773,0.1538647,0.004114104,0.001924266,0.005689987,0.007930956,0.00008369428],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.980547,0.0006537287,0.004449894,0.0005156464,0.0000240056,0.0002078649,0.0002217017,0.00006044154,0.01331975],"genre_scores_gemma":[0.9960741,0.000360332,0.002970473,0.00002927508,0.000010731,0.0001121129,0.00009613633,0.000006891562,0.0003401127],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004523413,"threshold_uncertainty_score":0.02392238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1724811041864772,"score_gpt":0.3458738475871783,"score_spread":0.1733927434007012,"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."}}