{"id":"W2135673422","doi":"10.5210/fm.v17i7.3968","title":"Materializing information: 3D printing and social change","year":2012,"lang":"en","type":"article","venue":"First Monday","topic":"Innovative Human-Technology Interaction","field":"Computer Science","cited_by":146,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Transformative learning; 3D printing; Section (typography); Process (computing); Session (web analytics); Key (lock); Focus (optics); Multimedia; Computer science; Sociology; World Wide Web; Engineering; Business; Advertising; Mechanical 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":["sts"],"consensus_categories":[],"category_scores_codex":[0.008733661,0.000452259,0.0004434837,0.004061455,0.01038535,0.01873029,0.001441915,0.004752026,0.01028581],"category_scores_gemma":[0.01379963,0.0002651406,0.0005207205,0.004619343,0.0489427,0.01509107,0.01084882,0.003057411,0.0007480782],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005915711,"about_ca_system_score_gemma":0.003294131,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003261014,"about_ca_topic_score_gemma":0.002615827,"domain_scores_codex":[0.9875874,0.008699549,0.0003238986,0.0008775652,0.00171962,0.0007919723],"domain_scores_gemma":[0.9846724,0.01063422,0.001575507,0.001295642,0.0008546626,0.0009676588],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00003757923,0.000108565,0.003510202,0.0003738483,0.00003422649,0.0007065394,0.2662793,0.0004238939,0.001058955,0.6556274,0.008507507,0.06333204],"study_design_scores_gemma":[0.00002809671,0.0001060208,0.004996725,0.0006150102,0.00002657005,0.0007413689,0.2144557,0.0007811725,0.001570348,0.2711466,0.5054575,0.00007501129],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2093249,0.01467266,0.01714409,0.1368114,0.0008321942,0.0001444667,0.0001424016,0.0001966155,0.6207314],"genre_scores_gemma":[0.9826075,0.003388899,0.002583076,0.002434225,0.0002658828,0.00006489697,0.00002740917,0.00004729129,0.008580799],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9896147,"threshold_uncertainty_score":0.04618853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03931359163958234,"score_gpt":0.2580522464633511,"score_spread":0.2187386548237688,"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."}}