{"id":"W4392721489","doi":"10.16995/intransition.15439","title":"Cutting Across Time: Oblique Editing in &lt;i&gt;Arrival&lt;/i&gt;","year":2023,"lang":"en","type":"article","venue":"[in]Transition","topic":"Digital Humanities and Scholarship","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bishop's University","funders":"","keywords":"Oblique case; Arrival time; Computer science; Engineering; Transport engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000908549,0.0002342873,0.0002990352,0.0003556767,0.0003015204,0.0006486159,0.000192893,0.0001164523,0.0007446091],"category_scores_gemma":[0.00004975955,0.0002567389,0.0001148631,0.0002408516,0.0001401048,0.001368007,0.00004505999,0.0003562788,0.0004763542],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000132606,"about_ca_system_score_gemma":0.0000330617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001633046,"about_ca_topic_score_gemma":0.01147053,"domain_scores_codex":[0.9979681,0.00009661506,0.0005452977,0.0003731345,0.0003075563,0.0007093104],"domain_scores_gemma":[0.9994578,0.0001357101,0.00008136669,0.0001856355,0.00007315649,0.00006629824],"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":[0.00024448,0.0006491423,0.001020462,0.0007618591,0.00005658783,0.001321334,0.5768126,0.003140818,0.01187243,0.3750096,0.008154213,0.02095655],"study_design_scores_gemma":[0.01223292,0.00110652,0.05362751,0.00759568,0.00008850867,0.00008753954,0.09887018,0.03329983,0.002246815,0.1650805,0.6203696,0.005394399],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8955765,0.0001029105,0.000008566229,0.0005846897,0.0004472197,0.000255865,0.0001216693,0.0002101577,0.1026924],"genre_scores_gemma":[0.9938645,0.00002578327,0.00001338388,0.0003863958,0.0009038247,0.00005326926,0.0002435067,0.00004805977,0.004461215],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6122153,"threshold_uncertainty_score":0.9999885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02871411319128281,"score_gpt":0.2450957503520772,"score_spread":0.2163816371607944,"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."}}