{"id":"W2786526525","doi":"10.5210/fm.v23i2.8073","title":"Goals for algorithmic genies","year":2018,"lang":"en","type":"article","venue":"First Monday","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Raising (metalworking); Computer science; Value (mathematics); Fundamental human needs; Data science; Risk analysis (engineering); Business; Engineering; Psychology","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":[0.01640296,0.001288914,0.0007469167,0.002161691,0.005899765,0.01167937,0.001833713,0.005927132,0.02122166],"category_scores_gemma":[0.03573756,0.0007686905,0.001445961,0.001412449,0.02323088,0.01686853,0.01314037,0.007249149,0.005452829],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004422575,"about_ca_system_score_gemma":0.005981373,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001497808,"about_ca_topic_score_gemma":0.00196038,"domain_scores_codex":[0.9885706,0.006257803,0.0005683182,0.00141888,0.002029974,0.00115428],"domain_scores_gemma":[0.982706,0.007490912,0.001084638,0.003943896,0.003089839,0.001684725],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000008800643,0.000007024418,0.0001357082,0.00002911463,0.00000408008,0.00001716834,0.0002369743,0.0006122598,0.00004909597,0.9921833,0.00278299,0.00393361],"study_design_scores_gemma":[0.000009011153,0.00001059356,0.00009349583,0.00007288917,0.000003923837,0.00002975796,0.0002959566,0.001067831,0.000110281,0.9446245,0.05367394,0.000007788248],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"commentary","genre_scores_codex":[0.01442202,0.002629287,0.2521242,0.06703321,0.00117183,0.0002615628,0.0002487459,0.0006529483,0.6614562],"genre_scores_gemma":[0.6324024,0.002678531,0.2489264,0.01603203,0.001101593,0.001515274,0.0005562413,0.001106736,0.09568085],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.02122166,"threshold_uncertainty_score":0.08674818,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05731704506763179,"score_gpt":0.4086526502802241,"score_spread":0.3513356052125923,"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."}}