{"id":"W2099706779","doi":"10.1109/icsm.2009.5306335","title":"Searching and skimming: An exploratory study","year":2009,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":75,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Formative assessment; Task (project management); Source code; Program comprehension; Exploratory research; Code (set theory); Task analysis; Software; Code review; Human–computer interaction; Software engineering; Static program analysis; Software development; World Wide Web; Data science; Software system; Programming language; Set (abstract data type); 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":["metaresearch","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.009328264,0.001005966,0.001263749,0.002520788,0.005813504,0.003343217,0.001998493,0.003306221,0.0019261],"category_scores_gemma":[0.04952028,0.001323613,0.0005071039,0.001464212,0.003285289,0.004638392,0.003047922,0.003050141,0.0007462196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009388465,"about_ca_system_score_gemma":0.001919632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00280533,"about_ca_topic_score_gemma":0.004306203,"domain_scores_codex":[0.9945769,0.002998033,0.000445634,0.0005523042,0.0008105636,0.0006164835],"domain_scores_gemma":[0.9525315,0.03891751,0.002522022,0.001514459,0.002764752,0.001749705],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0003756515,0.002378349,0.02683245,0.0006169529,0.00002752712,0.003258502,0.9403836,0.000114276,0.008860105,0.0006265119,0.0009449769,0.01558115],"study_design_scores_gemma":[0.0001881045,0.00442298,0.06340465,0.00054635,0.00006966773,0.005129472,0.8991248,0.001771998,0.005879446,0.001611707,0.01762351,0.0002272629],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961964,0.000116774,0.001574392,0.0002573735,0.000009222816,0.0004105375,0.0001086781,0.00004802419,0.001278562],"genre_scores_gemma":[0.9901738,0.0004571357,0.005526649,0.0006412963,0.00003881431,0.0008919479,0.0002168542,0.00007091517,0.001982586],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9966568,"threshold_uncertainty_score":0.04933316,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03435352700635105,"score_gpt":0.310245941000154,"score_spread":0.2758924139938029,"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."}}