{"id":"W4400142623","doi":"10.1145/3643834.3660736","title":"A Year of Interaction Around Town: Gathering Traces with an Interactive Knitting Machine and Community Stitch Markers","year":2024,"lang":"en","type":"article","venue":"Designing Interactive Systems Conference","topic":"Innovative Human-Technology Interaction","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; World Wide Web; Human–computer interaction","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":[],"consensus_categories":[],"category_scores_codex":[0.00139698,0.0006517063,0.0003155253,0.002363186,0.004862856,0.002496366,0.001118406,0.001404344,0.004710773],"category_scores_gemma":[0.006623677,0.0005023034,0.0003885418,0.002202628,0.002184829,0.002440857,0.002898675,0.00163765,0.00100122],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001106491,"about_ca_system_score_gemma":0.001075812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009128851,"about_ca_topic_score_gemma":0.04628101,"domain_scores_codex":[0.9986985,0.0005900043,0.00004943264,0.0002069335,0.0002721112,0.0001829644],"domain_scores_gemma":[0.9951037,0.002233335,0.0003702773,0.0007900101,0.0006508034,0.0008519453],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0005204216,0.0006178945,0.07390918,0.0007200873,0.0001227582,0.006215331,0.7296906,0.002396287,0.0233244,0.007283417,0.02064469,0.1345549],"study_design_scores_gemma":[0.00003620379,0.0008856245,0.1243371,0.0005806655,0.0001137987,0.002228782,0.5827935,0.005685424,0.01923208,0.004590176,0.2591931,0.0003236156],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9511611,0.0002281719,0.02786051,0.0008752425,0.0001148184,0.0003632598,0.002115257,0.0006118221,0.01666969],"genre_scores_gemma":[0.9516407,0.0002539775,0.03328633,0.0001930104,0.00004192639,0.0003324102,0.001384384,0.0003029182,0.0125642],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009128851,"threshold_uncertainty_score":0.0181514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04315458315134402,"score_gpt":0.296442076778895,"score_spread":0.253287493627551,"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."}}