{"id":"W2122467011","doi":"10.1145/2678025.2701387","title":"Exploring Personalized Command Recommendations based on Information Found in Web Documentation","year":2015,"lang":"en","type":"article","venue":"","topic":"Web Data Mining and Analysis","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Documentation; Computer science; Task (project management); World Wide Web; Software; Plan (archaeology); Feature (linguistics); Web application; Software documentation; Information retrieval; Human–computer interaction; Software system; Programming language; Software construction","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":[],"consensus_categories":[],"category_scores_codex":[0.0004550865,0.00006143822,0.00007406558,0.0002907489,0.00005596388,0.0002839447,0.0002200378,0.00001387871,0.00003162767],"category_scores_gemma":[0.00007043468,0.00005608181,0.00002021766,0.0005542864,0.000009110654,0.004008318,0.00004261244,0.00005645611,0.0001447699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008272185,"about_ca_system_score_gemma":0.00006981752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001412578,"about_ca_topic_score_gemma":0.00009574747,"domain_scores_codex":[0.9993453,0.00006323123,0.0001813935,0.0001071942,0.0002007871,0.0001020703],"domain_scores_gemma":[0.9995237,0.00007382855,0.00005389291,0.0002274875,0.00006283661,0.00005822985],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001500865,0.00064133,0.02053572,0.0000644505,0.00008522137,0.00001228575,0.03795175,0.04758086,0.0001102531,0.2703127,0.0910403,0.5315151],"study_design_scores_gemma":[0.001443294,0.00006367512,0.0009067542,0.00003436346,0.000004698789,7.082373e-7,0.001448847,0.9609569,0.00006826426,0.0003335481,0.03461004,0.0001289211],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04988215,0.000006147247,0.9174568,0.009233671,0.000296181,0.0001287349,0.00000670598,0.0001836229,0.02280598],"genre_scores_gemma":[0.9456481,0.000006624103,0.05290881,0.001072636,0.00001794843,0.00004124898,0.0001376706,0.000002450931,0.0001645125],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.913376,"threshold_uncertainty_score":0.2905934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1594357004825164,"score_gpt":0.3110716892556313,"score_spread":0.1516359887731149,"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."}}