{"id":"W1809680580","doi":"10.1111/j.1365-2575.2010.00368.x","title":"Using decision tree modelling to support Peircian abduction in IS research: a systematic approach for generating and evaluating hypotheses for systematic theory development","year":2011,"lang":"en","type":"article","venue":"Information Systems Journal","topic":"Advanced Text Analysis Techniques","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Virginia Commonwealth University","keywords":"Computer science; Data science; Management science; Development (topology); Empirical research; Decision tree; Development theory; Tree (set theory); Knowledge management; Data mining; Epistemology; Mathematics; 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":[],"consensus_categories":[],"category_scores_codex":[0.02101294,0.00020755,0.000594912,0.001498094,0.0007026994,0.0008684915,0.0005455319,0.00009859205,6.924062e-7],"category_scores_gemma":[0.001146252,0.0001661855,0.00009322692,0.0005763021,0.00001910839,0.003310176,0.00012175,0.0001891024,0.000003386889],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005096144,"about_ca_system_score_gemma":0.0002244153,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009867943,"about_ca_topic_score_gemma":0.000002585474,"domain_scores_codex":[0.9956416,0.0005335798,0.00222126,0.0002523149,0.000917112,0.0004341467],"domain_scores_gemma":[0.996485,0.0007222081,0.001045343,0.0003606206,0.001242655,0.0001441803],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002061703,0.0001392482,0.0001457452,0.1817772,0.0003186639,0.000004586223,0.2095926,0.549455,0.00125239,0.02521799,0.0000917242,0.03179856],"study_design_scores_gemma":[0.0003250922,0.0001344158,0.000004341103,0.01397177,0.00002617572,0.0002763088,0.006456154,0.9752992,0.0004897456,0.002821058,0.000004396214,0.0001913287],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01765436,0.0001441635,0.9778088,0.000004583391,0.0001210093,0.004103936,0.000001552282,0.00005822395,0.0001033889],"genre_scores_gemma":[0.3895341,0.000002316924,0.6096919,0.000024334,0.00004130623,0.0006814218,0.000001363742,0.00001090577,0.00001239895],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4258441,"threshold_uncertainty_score":0.8374884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4664136265099335,"score_gpt":0.4305231638408666,"score_spread":0.03589046266906687,"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."}}