{"id":"W2900958687","doi":"10.5771/9783956504211-256","title":"Historical ambiguity: a lens for approaching outdated terms","year":2018,"lang":"en","type":"book-chapter","venue":"Ergon Verlag eBooks","topic":"Reproductive Health and Technologies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ambiguity; Lens (geology); Through-the-lens metering; Computer science; Optics; Physics; Programming language","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003448927,0.000491393,0.000973277,0.0003456851,0.0001999632,0.00002151953,0.0002320545,0.000898935,0.00008213191],"category_scores_gemma":[0.0003414788,0.0004164161,0.0003530225,0.00001774322,0.0002389916,0.00003803808,0.0001369033,0.0008313109,0.0001097603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009415484,"about_ca_system_score_gemma":0.0002649124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003302415,"about_ca_topic_score_gemma":0.00001051949,"domain_scores_codex":[0.9975371,0.0000130928,0.0005821361,0.0009893113,0.0003571853,0.0005211218],"domain_scores_gemma":[0.9980335,0.00005928258,0.0003428417,0.001161352,0.0002296853,0.0001733715],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.004621897,0.0002680546,0.0002565721,0.00431643,0.001165231,0.0003404652,0.001244665,2.768599e-7,0.00185994,0.2485947,0.4494947,0.2878371],"study_design_scores_gemma":[0.001023534,0.001196515,0.00006976343,0.000331761,0.0002391493,0.00008090556,0.00001235466,0.000007664329,0.0006823709,0.01948809,0.976477,0.000390836],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001679454,0.0007960839,0.0006318075,0.0008986758,0.001634883,0.002416787,0.00004159949,0.001004266,0.9908965],"genre_scores_gemma":[0.00768636,0.00004700544,0.003156159,0.0005417115,0.002076818,0.0001620883,0.00008133973,0.0001753617,0.9860731],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.5269824,"threshold_uncertainty_score":0.9998288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08642096945022965,"score_gpt":0.2939059334778505,"score_spread":0.2074849640276208,"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."}}