{"id":"W7038219141","doi":"","title":"“Goodbye to All That”: Propertius’ <italic>magnum iter</italic> between <italic>Elegies</italic> 3.16 and 3.21","year":2017,"lang":"en","type":"article","venue":"Project Muse (Johns Hopkins University)","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Volume (thermodynamics); Association (psychology); Set (abstract data type); Perspective (graphical); Work (physics)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001710595,0.0006998815,0.0004066419,0.0009577158,0.004214119,0.005266435,0.0006779064,0.001698089,0.02860347],"category_scores_gemma":[0.004163442,0.0003725299,0.0003777728,0.0009178922,0.01011976,0.009189126,0.002644489,0.006076739,0.0109529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004217078,"about_ca_system_score_gemma":0.002083757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01158917,"about_ca_topic_score_gemma":0.0285032,"domain_scores_codex":[0.9987291,0.0004790279,0.00005804748,0.0002352805,0.0003594288,0.0001390397],"domain_scores_gemma":[0.9991747,0.0002622361,0.00006679388,0.000163767,0.0002439063,0.0000885684],"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":[0.00003369344,0.00001009618,0.0001823724,0.00007519799,0.000007035049,0.00006176345,0.004136609,0.0000390657,0.0002064614,0.4268308,0.5461763,0.02224062],"study_design_scores_gemma":[0.000003509423,0.000006080568,0.0002607947,0.00008796699,0.00000320016,0.0001140884,0.0008301249,0.00006125287,0.0001996418,0.02636965,0.9720545,0.000009028761],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.004594372,0.03151835,0.01510184,0.1255454,0.03071657,0.00005311946,0.0003763996,0.0006900703,0.7914039],"genre_scores_gemma":[0.1445921,0.0109884,0.008021411,0.02942065,0.009793178,0.00009422979,0.0003963257,0.002732716,0.7939609],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02860347,"threshold_uncertainty_score":0.0956881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03420331903693148,"score_gpt":0.2604198371137705,"score_spread":0.2262165180768391,"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."}}