{"id":"W1985407034","doi":"10.3138/carto.43.2.107","title":"Approximating Cartography to the Customer's Expectations: Applying the “House of Quality” to Map Design","year":2008,"lang":"en","type":"article","venue":"Cartographica The International Journal for Geographic Information and Geovisualization","topic":"Quality Function Deployment in Product Design","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quality function deployment; House of Quality; Competitor analysis; Product (mathematics); Quality (philosophy); Voice of the customer; Product planning; New product development; Computer science; Order (exchange); Product design; Process (computing); Set (abstract data type); Process management; Engineering; Marketing; Business; Service quality; Service (business); Mathematics; Customer advocacy; Customer retention","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.003672053,0.0002338456,0.0002162662,0.00140948,0.001800484,0.0007828405,0.0008502452,0.00006873566,0.0000215308],"category_scores_gemma":[0.001053497,0.0001390964,0.0002619658,0.00190562,0.0002069889,0.001683197,0.000155957,0.0002261517,0.00004305525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002282108,"about_ca_system_score_gemma":0.00004751638,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001560323,"about_ca_topic_score_gemma":0.00003127278,"domain_scores_codex":[0.99708,0.0001303637,0.001190504,0.0001961427,0.001114424,0.0002886117],"domain_scores_gemma":[0.9961085,0.0004600798,0.0009702911,0.0003396891,0.002077,0.0000443872],"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":[0.002088671,0.0004190358,0.06235515,0.0005052762,0.001971223,0.000003891317,0.03753783,0.06856791,0.0009011558,0.5902945,0.1716212,0.06373412],"study_design_scores_gemma":[0.001815358,0.0001587655,0.01248669,0.000186578,0.0002621156,0.0001343057,0.02393188,0.01779609,0.0003159389,0.01351418,0.9286565,0.0007416242],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1035891,0.0004260998,0.8360359,0.04759616,0.004921868,0.006601361,0.00003724392,0.0003373538,0.0004549185],"genre_scores_gemma":[0.9779146,0.0001450672,0.001587894,0.01785478,0.001161259,0.001184718,0.00007093357,0.00003841822,0.00004227863],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8743255,"threshold_uncertainty_score":0.999499,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04339928100756472,"score_gpt":0.2933182273123916,"score_spread":0.2499189463048269,"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."}}