{"id":"W3197695904","doi":"10.1115/1.4052297","title":"Queries and Cues: Textual Stimuli for Reflective Thinking in Digital Mind-Mapping","year":2021,"lang":"en","type":"article","venue":"Journal of Mechanical Design","topic":"Creativity in Education and Neuroscience","field":"Psychology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Directorate for Education and Human Resources","keywords":"Computer science; Workflow; Human–computer interaction; Ontology; Mind map; Cognition; Task (project management); Focus (optics); Cognitive science; Graph; Interface (matter); Artificial intelligence; Psychology; Epistemology; Theoretical computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00274101,0.0007382829,0.0004068429,0.0007281344,0.0005360487,0.002334497,0.001385855,0.001385886,0.0162153],"category_scores_gemma":[0.04149577,0.0002448369,0.0003503071,0.0005992885,0.001315162,0.003617407,0.003770173,0.0008790088,0.001194174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000561581,"about_ca_system_score_gemma":0.0005070789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004222243,"about_ca_topic_score_gemma":0.0004338279,"domain_scores_codex":[0.9975708,0.001555526,0.0001487618,0.0002819694,0.0003129504,0.0001298605],"domain_scores_gemma":[0.9677464,0.02863738,0.0007327709,0.001533854,0.0007526629,0.0005968959],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.008826066,0.001732899,0.006142053,0.007975035,0.00009115836,0.002311298,0.07947369,0.01559238,0.2009911,0.0926523,0.01705067,0.5671613],"study_design_scores_gemma":[0.003459386,0.008082597,0.02587524,0.003708987,0.0004598047,0.002174492,0.04078605,0.2274238,0.1739091,0.2436204,0.2694635,0.00103656],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6082084,0.0009489244,0.3293431,0.00158164,0.0004525265,0.002206188,0.0009649352,0.007693068,0.04860129],"genre_scores_gemma":[0.8214067,0.0002404625,0.1712153,0.0005564069,0.00005973188,0.001263249,0.0004067105,0.0005912246,0.00426019],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0162153,"threshold_uncertainty_score":0.05424559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1231550596380405,"score_gpt":0.3999097496390889,"score_spread":0.2767546900010484,"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."}}