{"id":"W4414586197","doi":"10.1002/spe.70024","title":"Project Templating and Onboarding With Cookiecutter: Foundations, Uses, and Guidelines","year":2025,"lang":"en","type":"article","venue":"Software Practice and Experience","topic":"Advanced Software Engineering Methodologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Telus (Canada); Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Onboarding; Context (archaeology); Python (programming language); Web application; Software; Quality (philosophy); Metadata","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0278919,0.001145139,0.0005549862,0.004268575,0.00200534,0.007763871,0.003929888,0.001832624,0.008571024],"category_scores_gemma":[0.09481941,0.00181279,0.0009539906,0.002905168,0.006346919,0.01280594,0.00754882,0.003312259,0.005841412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002408856,"about_ca_system_score_gemma":0.005812016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004547908,"about_ca_topic_score_gemma":0.009518498,"domain_scores_codex":[0.9793984,0.008996656,0.002815222,0.001989137,0.005622077,0.001178495],"domain_scores_gemma":[0.914752,0.04192128,0.004870123,0.02422675,0.01031857,0.003911269],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004097661,0.0004150063,0.02008856,0.002569964,0.00006928447,0.0008909757,0.03131756,0.006836376,0.01461257,0.2232422,0.07205747,0.6274902],"study_design_scores_gemma":[0.0001048148,0.0003427536,0.01126931,0.004153264,0.0000723476,0.002799286,0.008095164,0.03622073,0.03391504,0.1249156,0.7775561,0.0005556447],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.038783,0.001304107,0.862175,0.004557137,0.0001807307,0.00125243,0.0007067141,0.04595055,0.04509032],"genre_scores_gemma":[0.1182049,0.001101485,0.8511069,0.0007531365,0.00007502901,0.001188371,0.001477612,0.01202143,0.01407103],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0278919,"threshold_uncertainty_score":0.1475081,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06036869627729666,"score_gpt":0.3940579685862917,"score_spread":0.333689272308995,"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."}}