{"id":"W3094979386","doi":"","title":"Approaching Roles with Affordances","year":2020,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Complex Systems and Decision Making","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Affordance; Computer science; Human–computer interaction","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","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.01617625,0.000526505,0.0009342133,0.0004314424,0.0006579501,0.002845005,0.00401935,0.000269701,0.000316372],"category_scores_gemma":[0.008078631,0.0004001575,0.0003909741,0.001117331,0.000298145,0.0003096243,0.00357033,0.0009874681,0.0002239932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000860892,"about_ca_system_score_gemma":0.0004426213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005953017,"about_ca_topic_score_gemma":0.002244108,"domain_scores_codex":[0.9860448,0.007518239,0.00138125,0.001910017,0.002654768,0.0004909649],"domain_scores_gemma":[0.984451,0.006598505,0.00151695,0.00385018,0.003200962,0.0003824223],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00009207764,0.000586269,0.01372653,0.000201662,0.000231611,0.00006266708,0.02865968,0.002782562,0.001246206,0.6705742,0.01820986,0.2636266],"study_design_scores_gemma":[0.001879731,0.000003056582,0.01609623,0.006419904,0.0001295421,0.0001131635,0.004340632,0.2730012,0.00733145,0.4855767,0.2025765,0.002531809],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05303697,0.002354496,0.7925436,0.01009537,0.0003484669,0.0006096817,0.00006599378,0.0003286426,0.1406167],"genre_scores_gemma":[0.8660641,0.00003976033,0.1230157,0.0001648068,0.00007607902,0.00006717029,0.00004858641,0.00005827207,0.01046552],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8130271,"threshold_uncertainty_score":0.999845,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07827060445716078,"score_gpt":0.3113205878887202,"score_spread":0.2330499834315595,"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."}}