{"id":"W3005569205","doi":"","title":"Optimising Performance: How Jungian Alchemy Informs Organisational Transformation","year":2020,"lang":"en","type":"article","venue":"Digital WPI","topic":"Innovation, Sustainability, Human-Machine Systems","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Alchemy; Organizational change; Work (physics); Transformation (genetics); Process (computing); Psychology; Sociology; Aesthetics; Social psychology; Public relations; Political science; Computer science; Engineering; Art; Mechanical engineering; Literature","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":[0.0004200219,0.0001294424,0.0001367761,0.00008661287,0.0005655502,0.0008022335,0.0002399589,0.00009163743,0.0001130591],"category_scores_gemma":[0.0004778639,0.0001251137,0.00006051556,0.0007103429,0.0001594147,0.003837544,0.00002903645,0.0001389462,0.00008551359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002773239,"about_ca_system_score_gemma":0.0003664905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000501933,"about_ca_topic_score_gemma":0.00001563306,"domain_scores_codex":[0.9985188,0.00002577758,0.0002971433,0.0001732182,0.0006727927,0.0003122287],"domain_scores_gemma":[0.9992137,0.00004051817,0.0001128574,0.000101224,0.0004019813,0.0001297092],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008534196,0.0001450037,0.05274771,0.000698906,0.00008475543,0.000004946567,0.5947672,0.00177405,0.000190371,0.260877,0.005268509,0.08335619],"study_design_scores_gemma":[0.002376145,0.0004637254,0.03836145,0.0001121125,0.00003754335,0.000012698,0.2319977,0.01850808,0.002017754,0.006524928,0.6977235,0.001864303],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7614538,0.00001133091,0.005071087,0.01611699,0.0002376413,0.0006191069,0.00002507827,0.0002845698,0.2161804],"genre_scores_gemma":[0.9981166,0.000002713175,0.0001139996,0.0003979297,0.0004529585,0.000009683814,0.0001744207,0.00001442612,0.0007173232],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.692455,"threshold_uncertainty_score":0.7735956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02559318510297365,"score_gpt":0.2719061835468296,"score_spread":0.246312998443856,"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."}}