{"id":"W4402136389","doi":"10.1007/s10664-024-10528-7","title":"Consensus task interaction trace recommender to guide developers’ software navigation","year":2024,"lang":"en","type":"article","venue":"Empirical Software Engineering","topic":"Software Engineering Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Concordia University; Polytechnique Montréal","funders":"","keywords":"TRACE (psycholinguistics); Recommender system; Computer science; Task (project management); Software; World Wide Web; Human–computer interaction; Software engineering; Data science; Engineering; Programming language; Systems 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005957409,0.0003853783,0.000293235,0.0005083413,0.0001193975,0.0005460621,0.0008081369,0.0001854204,0.00004640273],"category_scores_gemma":[0.004590492,0.0003940424,0.0001413368,0.001818123,0.00001888799,0.000525048,0.0004117959,0.0007662778,0.000649775],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008342298,"about_ca_system_score_gemma":0.0002100071,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003110136,"about_ca_topic_score_gemma":0.000002101601,"domain_scores_codex":[0.9971571,0.00005385943,0.0005089015,0.0008998078,0.0006270838,0.0007532681],"domain_scores_gemma":[0.9957399,0.00298718,0.00002958805,0.0006313734,0.0001718974,0.0004399992],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003818832,0.0001879178,0.03159457,0.001182421,0.0004559421,0.001517839,0.009180169,0.4154736,0.003083077,0.0006171853,0.2801127,0.2565564],"study_design_scores_gemma":[0.0003605945,0.0001976196,0.0236855,0.00105148,0.00002276327,0.0005426101,0.00005489806,0.164816,0.002909241,0.0001645668,0.8047414,0.0014533],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05230176,0.0005247288,0.9371352,0.002331193,0.002486274,0.0003084714,0.00001039812,0.004877973,0.0000239697],"genre_scores_gemma":[0.3929146,0.0000111576,0.6051924,0.0004386405,0.0004148858,0.0001633549,0.00002691153,0.0001377072,0.0007004195],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5246287,"threshold_uncertainty_score":0.9998512,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03634913362255968,"score_gpt":0.3289170491667666,"score_spread":0.2925679155442069,"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."}}