{"id":"W1559483088","doi":"10.46430/phen0013","title":"Manipulating Strings in Python","year":2012,"lang":"en","type":"article","venue":"The Programming Historian","topic":"Computational Physics and Python Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Python (programming language); Programming language; Computer science","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":[0.001249506,0.0008275668,0.0004789946,0.0008988561,0.001407233,0.002286032,0.00143443,0.0007365907,0.03016322],"category_scores_gemma":[0.004739321,0.0006110458,0.00115332,0.001488025,0.002606603,0.006721996,0.00276131,0.004377566,0.01599929],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005265827,"about_ca_system_score_gemma":0.001717317,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007812678,"about_ca_topic_score_gemma":0.000792797,"domain_scores_codex":[0.9987819,0.0002374778,0.00009498374,0.0001850458,0.0006038735,0.00009671591],"domain_scores_gemma":[0.9990547,0.0004157082,0.00005309041,0.0002089915,0.000187319,0.00008011903],"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":[0.00007164032,0.00006511166,0.0004883276,0.0008229327,0.00004293037,0.0003034481,0.001245367,0.003127033,0.007881175,0.4909017,0.2029013,0.2921491],"study_design_scores_gemma":[0.00001488265,0.00002683051,0.0002860777,0.000242766,0.00001207674,0.0005654449,0.0001261271,0.004050691,0.006979051,0.2233073,0.7643243,0.00006452751],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002562213,0.002711228,0.8759722,0.006283114,0.002437296,0.0001019971,0.001266887,0.01962516,0.08903982],"genre_scores_gemma":[0.04961574,0.01060995,0.8008658,0.007260801,0.001935297,0.0005122278,0.002369934,0.0116006,0.1152296],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03016322,"threshold_uncertainty_score":0.1009061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02827235117137446,"score_gpt":0.2650164729763786,"score_spread":0.2367441218050041,"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."}}