{"id":"W3172254362","doi":"10.29173/irie415","title":"Constructing AI: Examining how AI is shaped by data, models and people","year":2021,"lang":"en","type":"article","venue":"The International Review of Information Ethics","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Construct (python library); Context (archaeology); Artificial intelligence; Computer science; Data science; Big data; Data mining","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.004885612,0.00007008304,0.000159996,0.00002582047,0.0003716944,0.0003505757,0.000535496,0.000127095,0.0001498109],"category_scores_gemma":[0.01155798,0.00005758815,0.00003289404,0.0001607802,0.0002553325,0.003163274,0.0002370044,0.000613369,0.000005577037],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005173038,"about_ca_system_score_gemma":0.0007320518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005534129,"about_ca_topic_score_gemma":0.0005401064,"domain_scores_codex":[0.9983235,0.0001978102,0.0003455097,0.0000854324,0.0009335548,0.000114171],"domain_scores_gemma":[0.9964724,0.001098123,0.0003373916,0.0002046042,0.001834092,0.0000534031],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00000306583,0.00001076538,0.0002484137,0.0009596575,0.00007285258,2.960422e-7,0.0635938,0.000004202795,0.00001847319,0.873433,0.03213594,0.02951953],"study_design_scores_gemma":[0.0005826773,0.00003543717,0.0002212154,0.007822265,0.0001331187,0.00002157314,0.1064788,0.02568819,0.0002371496,0.1455067,0.7127607,0.0005121769],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.001954542,0.006811212,0.01370355,0.9193701,0.0004856605,0.0002493663,0.0003573896,0.00002915096,0.05703904],"genre_scores_gemma":[0.6451833,0.189168,0.001391737,0.1630122,0.0001846638,0.000007571135,0.0005244139,0.000008768599,0.0005193354],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.7563578,"threshold_uncertainty_score":0.9967681,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1607524166623108,"score_gpt":0.4325197418316919,"score_spread":0.2717673251693811,"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."}}