{"id":"W2890889925","doi":"10.1145/3235765.3235767","title":"Documenting trajectories in design space","year":2018,"lang":"en","type":"article","venue":"","topic":"Innovative Human-Technology Interaction","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Materiality (auditing); Witness; Computer science; Perspective (graphical); Space (punctuation); Game design; Work (physics); Game mechanics; Human–computer interaction; Engineering; Aesthetics; Artificial intelligence; Programming language; Mechanical 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007443027,0.0008123678,0.0005201254,0.004987293,0.003004484,0.01075465,0.001660703,0.001606564,0.01579439],"category_scores_gemma":[0.05037085,0.001069625,0.0007933242,0.004899067,0.008092356,0.01851683,0.006444752,0.003584159,0.002534493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005114758,"about_ca_system_score_gemma":0.005077832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0121437,"about_ca_topic_score_gemma":0.01713489,"domain_scores_codex":[0.9925339,0.003580672,0.0004044553,0.001301797,0.001812906,0.0003662812],"domain_scores_gemma":[0.9679931,0.01763288,0.001947313,0.007125722,0.004577133,0.0007239095],"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":[0.0001247343,0.00008037204,0.00984637,0.000352431,0.00003396491,0.0001787412,0.03677638,0.0085385,0.001128312,0.845287,0.004754442,0.09289877],"study_design_scores_gemma":[0.00004120122,0.0001287832,0.004237022,0.0007209415,0.00002613078,0.0001988514,0.02659586,0.03066983,0.002175362,0.7558051,0.1793342,0.00006673799],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1799198,0.004095843,0.6373675,0.008491172,0.0002423606,0.0006245804,0.002813209,0.001346068,0.1650995],"genre_scores_gemma":[0.6705409,0.002511246,0.3071591,0.0002461559,0.00002544477,0.0007572025,0.002674486,0.0008194514,0.01526599],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01579439,"threshold_uncertainty_score":0.05283749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03051361126040763,"score_gpt":0.2952873701405393,"score_spread":0.2647737588801317,"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."}}